Harmonic Mean Operators for Aggregating Linguistic Information

Size: px
Start display at page:

Download "Harmonic Mean Operators for Aggregating Linguistic Information"

Transcription

1 Fourth Iteratoal Coferece o Natural Computato Harmoc Mea Operator for Aggregatg Lgutc Iformato Zehu Xu College of Ecoomc ad Maagemet Southeat Uverty, Nag, Jagu 0096, Cha E-mal: xu_zehu@63.et Abtract Harmoc mea wdely ued to aggregate cetral tedecy data, whch uually expreed exact umercal value. I th paper, we vetgate the tuato where the put data are gve the form of lgutc label, ad develop ome lgutc harmoc mea aggregato operator, uch a the lgutc weghted harmoc mea (LWHM operator, the lgutc ordered weghted harmoc mea (LOWHM operator, ad the lgutc hybrd harmoc mea (LHHM operator for aggregatg lgutc formato. Some example are gve to llutrate the developed operator.. Itroducto Over the lat decade, may operator have bee developed for aggregatg umercal data formato [], where the weghted averagg operator, the ordered weghted averageg operator, the weghted harmoc mea operator, the weghted geometrc mea operator, ad the ordered weghted geometrc mea operator are fve of the mot commo aggregato operator the formato fuo lterature [-7]. The weghted averagg operator [] ad the weghted geometrc mea operator [5] are the aggregato techque whch take to accout all the gve umercal data together wth ther weght. The ordered weghted averagg (OWA operator [3] wa troduced to provde a method for aggregatg everal put that le betwee the max ad m operator, whoe fudametal apect the re-orderg tep, that, the OWA operator frt reorder all the gve data decedg order, ad the aggregate the reordered data together wth the weght of ther poto, the ordered weghted geometrc mea operator [6,7] baed o the OWA operator ad o the geometrc mea, whch ha ome mlar charactertc wth the OWA operator. The weghted harmoc mea operator [4] a coervatve average, whch wdely ued to aggregate cetral tedecy data. I the real-lfe world, there are may tuato, uch a electg applcato for dfferet kd of cholarhp ad electg proect for dfferet kd of fudg polce, ad evaluatg the peed, comfort or deg for dfferet kd of car, whch a more realtc approach may be to ue lgutc aemet tead of umercal value [8]. Some author [8-7] exteded the weghted averagg operator, the ordered weghted averageg operator, the weghted geometrc mea operator, ad the ordered weghted geometrc mea operator to accommodate the tuato where the put data are expreed lgutc label, ad appled the exteded operator for olvg varou deco makg problem uder lgutc evromet. I th paper, we exted the well-kow harmoc mea to accommodate lgutc tuato, ad develop ome lgutc harmoc mea aggregato operator, uch a the lgutc weghted harmoc mea (LWHM operator, the lgutc ordered weghted harmoc mea (LOWHM operator, ad the lgutc hybrd harmoc mea (LHHM operator for aggregatg lgutc formato. The charactertc of thee developed operator are alo aalyzed.. Prelmare For coveece, we frt recall ome bac oto ad operato related to lgutc formato, whch wll be ued th paper: Lgutc label are a bac tool ued to decrbe the qualtatve apect of a problem. I [8], Xu defed S { t,...,,,,..., t} a a lgutc label et wth odd cardalty. Ay label,, repreet a poble value for a lgutc varable, ad t requred that the lgutc label et hould atfy the followg charactertc: > β ff > β ; There the recprocal operator: rec( β uch that β. Epecally, rec(, where the md /08 $ IEEE DOI 0.09/ICNC

2 lgutc label repreet a aemet of dfferece, ad wth the ret of the lgutc label beg placed recprocally aroud t. I partcular, t ad t dcate the lower ad upper lmt of the lgutc label S, repectvely, t a potve teger, ad the cardalty of S t. For example, a et of e lgutc label could be a follow: S { oe, very low, low, lghtly low, medum, lghtly hgh, 3 hgh, 4 5 very hgh, perfect} Xu [85] exteded the dcrete lgutc label et S to a cotuou label et S { [ q, q]} o a to preerve all the gve formato, where q ( q > t a uffcetly large potve teger. If S, the termed a orgal lgutc label, otherwe, termed a vrtual lgutc label. I geeral, the vrtual lgutc label ca oly appear calculato. If, β S, λ [0,], the ther operatoal law were defed a follow [8]: β ; + β λ λ ; 3 (. 3. Lgutc harmoc mea aggregato operator Baed o the well-kow harmoc mea [4], the followg, we develop ome operator for aggregatg lgutc formato: Defto. Let LWHM : S S, ad (,,..., be a collecto of lgutc label. If LWHM (,,..., ( w( w( w ( ( the LWHM called a lgutc weghted harmoc mea (LWHM operator, where w ( w, w,..., w T the weght vector aocated wth the lgutc label (,,...,, w 0,,,...,, ad w. Baed o the operatoal law of the lgutc label, we ca traform ( to the followg: LWHM (,,..., ( w( w ( w ( ( w w w ( w w w ( w where. a By Defto, we have the followg cocluo for ome pecal cae: If w, w 0,, the LWHM (,,..., (3 If w (,,..., T, the the LWHM operator reduced to the lgutc harmoc mea (LHM operator: LWHM (,,..., where ( w( w ( w ( ( ( ( ( LHM (,,..., (4. a Moreover, the LWHM operator a bouded operator whch provde for aggregato lyg betwee the lgutc max operator ad the lgutc m operator: m{ } LWHM (,,..., max{ } (5 I fact, by the operatoal law of the lgutc label, we have LWHM (,,..., ( w( w( w ( ( w(max{ } (max{ } (max{ } w w ( ( (max{ } w w w ad max{ } LWHM (,,..., 05

3 ( w( w( w ( ( (m{ } (m{ } w (m{ } w w ( ( (m{ } w w w m{ } thu, (5 hold. The LWHM operator aggregate all the gve lgutc label together wth ther aocated weght. It a coervatve average, whch very utable to be ued a a tool to aggregate cetral tedecy data. Example. Gve a collecto of fve lgutc label:, 3,,, 4, let w (0.3, 0.,0.,0.3,0. T be the weght vector of (,,3,4,5, the by (, we have LWHM(,,,, ( w( w( w3( w4( w5( ( 0.3 ( 0. ( 3 0. ( ( 0. ( Motvated by the ordered weghted averagg (OWA operator [3], here we defe a lgutc ordered weghted harmoc mea (LOWHM operator: Defto. A lgutc ordered weghted harmoc mea (LOWHM operator of dmeo a mappg LOWHM : S S, that ha a aocated vector ω ( ω, ω,..., ω T uch that ω 0,,,...,, ad ω. Moreover, LOWHM (,,..., ( ω ( σ ( ω ( σ ( ω ( σ ( (6 where (,,..., be a collecto of lgutc label. ( σ (, σ (,..., σ ( a permutato of (,,..., uch that, for all. σ ( σ( Baed o the operatoal law of the lgutc label, (6 ca be further traformed to the followg: LOWHM (,,..., (7 ω where. σ ( The aocated vector ω ( ω, ω,..., ω T ca be determed by ug ome weght determg method, for example, O Haga [9] developed a procedure to geerate the weght that have a predefed degree of ore ad maxmze the etropy of the weght. Flev ad Yager [0] developed two procedure, baed o the expoetal moothg, to obta the weght. Yager [] troduced a bac ut-terval mootoc (BUM fucto baed approach to determg the weght. Xu [] made a urvey of the weght determg method ad the developed a ormal dtrbuto baed method, whch ca releve the fluece of the ufar argumet by agg low weght to thoe fale or baed oe. By Defto, we have If ω (,0,...,0 T, the LOWHM (,,..., max{ } (8 If ω (0,0,..., T σ(, the LOWHM (,,..., m{ } (9 σ( 3 If ω 0, ω 0,, the LOWHM (,,..., σ( (0 4 If ω (,,..., T, the the LOWHM operator reduced to the LHM operator: LOWHM (,,..., LHM (,,..., ( Furthermore, the LOWHA operator ha ome derable properte mlar to thoe of the OWA operator [3]: (Idempotecy: Let (,,..., be a collecto of lgutc label, f all (,,..., are equal,.e.,, for all, the LOWHM (,,..., ( (Boudary: Let (,,..., be a collecto of lgutc label, the m{ } LOWHM (,,..., max{ } (3 σ( σ( * * (,,..., ad 3 (Mootocty: Let (,, *..., be two collecto of lgutc label, f *, for all, the * * * LOWHM (,,..., LOWHM (,,..., (4 06

4 4 (Commutatvty: Let (,,..., be a collecto of lgutc label, the LOWHM LOWHM (5 ' ' ' (,,..., (,,..., ' ' ' where (,,..., ay permutato of (,,...,. The LOWHM operator alo provde a techque for fug the gve lgutc label that le betwee the max ad m lgutc aggregato operator. Smlar to the Yager OWA operator, the fudametal apect of the LOWHM operator the re-orderg tep, that, the LOWHM operator frt reorder all the gve lgutc label decedg order, ad the aggregate the reordered lgutc label together wth the weght of ther poto. Example. Gve a collecto of four lgutc label: 3, 4, 3, 4. We frt rak the lgutc label (,,3,4 decedg order:, ( 3 σ ( 3 4 ( 3 σ, σ ( 4 4 σ Let ω (0.55,0.345,0.345,0.55 T be the aocated vector of the LOWHM operator derved from the ormal dtrbuto baed method [], the by (6, we have LOWHM (,,, 3 4 ( ω ( σ( ω ( σ( ω3 ( σ( 3 ω4 ( σ( 4 ( 0.55 ( ( ( 0.55 ( I what follow, we troduce aother lgutc harmoc mea aggregato operator lgutc hybrd harmoc mea (LHHM operator, whch baed o the LWHM ad LOWHM operator: Defto 3. A lgutc hybrd harmoc mea (LHHM operator of dmeo a mappg LHHM : S S, whch ha a aocated vector ω ( ω, ω,..., ω T wth ω 0,,,...,, ad ω, uch that LHHM (,,..., ( ω ( σ ( ω ( σ ( ω ( σ ( (6 where σ ( the th larget of the weghted lgutc label ( w,,,...,, w ( w, w,..., w T the weght vector of the lgutc label (,,..., w,,,...,, ad, wth 0 w. Epecally, f w (,,..., T, the,,,...,, th cae, the LHHM operator reduced to the LOWHM operator; f ω (,,..., T, the the LHHM operator reduced to the LWHM operator. Obvouly, the LHHM operator geeralze the LOWHM ad LWHM operator, ad reflect the mportace of both the gve lgutc label ad ther ordered poto. Example 3. let 4,, 3 3,, 4 5 4, ad be a collecto of x 6 lgutc label, ad let w (0.0,0.5,0.0,0.0,0.0,0.5 T be the weght vector of (,,...,6, the the weghted lgutc label ( 6w,,,..., 6 are a follow: , , , , We rak the weghted lgutc label decedg order: ( (,,...,6,, σ, ( σ σ ( 4.4 ( σ ( 3 3.8, σ σ ( Let ω (0.09,0.7,0.4,0.4,0.7,0.09 T be the aocated vector of the LHHM operator derved from the ormal dtrbuto baed method [9], the by (6, we have LHHM (,,..., 6 ( ω ( σ ( ω ( σ ( ω6 ( σ ( 6 ( 0.09 ( ( ( ( ( (

5 4. Cocluo Harmoc mea oe of the mot commoly-ued meaure of cetral tedecy. Coder that, real-lfe tuato, the put data are uually expreed lgutc label tead of umercal value, th paper we have exteded the tradtoal harmoc mea to deal wth lgutc formato. We have developed ome lgutc harmoc mea aggregato operator, cludg the lgutc weghted harmoc mea (LWHM operator, the lgutc ordered weghted harmoc mea (LOWHM operator, ad the lgutc hybrd harmoc mea (LHHM operator for aggregatg lgutc formato. Moreover, we have aalyzed the charactertc of the developed operator,.e., the LWHM operator drectly aggregate all the gve lgutc label together wth ther aocated weght; the LOWHM operator frt reorder all the gve lgutc label decedg order, ad the aggregate the reordered lgutc label together wth the weght of ther poto, the fudametal apect of the LOWHM operator the re-orderg tep; whle the LHHM operator geeralze both the LWHM ad LOWHM operator, ad emphaze the mportace of both the gve lgutc label ad ther ordered poto. I the future reearch, thee lgutc harmoc mea aggregato operator ca be appled may feld uch a deco makg, medcal dago, data mg, ad oft computg, etc. Ackowledgemet The work wa upported by the Natoal Natural Scece Foudato of Cha (No ad the Natoal Scece Fud for Dtguhed Youg Scholar of Cha (No Referece [] Z.S. Xu ad Q.L. Da, A overvew of operator for aggregatg formato, Iteratoal Joural of Itellget Sytem, 003, 8: [] J.C. Haray, Cardal welfare, dvdualtc ethc, ad terperoal comparo of utlty, Joural of Poltcal Ecoomy, 955, 63: [3] R.R. Yager, O ordered weghted averagg aggregato operator mult-crtera deco makg, IEEE Traacto o Sytem, Ma, ad Cyberetc, 988, 8: [4] P.S. Bulle, D.S. Mtrovć, ad P.M. Vać, Mea ad Ther Iequalte, Redel, Dordrecht, 988. [5] T.L. Saaty, The Aalytc Herarchy Proce, McGraw-Hll, New York, 980. [6] F. Herrera, E. Herrera-Vedma, ad F. Chclaa, Multpero deco-makg baed o multplcatve preferece relato, Europea Joural of Operatoal Reearch, 00, 9: [7] Z.S. Xu ad Q.L. Da, The ordered weghted geometrc averagg operator, Iteratoal Joural of Itellget Sytem, 00, 7: [8] Z.S. Xu, Lgutc aggregato operator: a overvew, I: Fuzzy Set ad Ther Exteo: Repreetato, Aggregato ad Model (Edtor: H. Butce, F. Herrera, ad J. Motero, Sprger-Verlag, 007, pp [9] M. Delgado, J.L. Verdegay, ad M.A. Vla, O aggregato operator of lgutc label, Iteratoal Joural of Itellget Sytem, 993, 8: [0] G. Bordoga, M. Fedrzz, ad G. Pa, A lgutc modelg of coeu group deco makg baed o OWA operator, IEEE Traacto o Sytem, Ma, ad Cyberetc-Part A, 997, 7: 6-3. [] F. Herrera ad E. Herrera-Vedma, Aggregato operator for lgutc weghted formato, IEEE Traacto o Sytem, Ma, ad Cyberetc-Part A, 997, 7: [] F. Herrera ad L. Martíez, A -tuple fuzzy lgutc repreetato model for computg wthword, IEEE Traacto o Fuzzy Sytem, 000, 8: [3] F. Herrera ad L.A. Martíez, A model baed o lgutc -tuple for dealg wth multgraular herarchcal lgutc cotext mult-expert deco makg, IEEE Traacto o Sytem, Ma, ad Cyberetc-Part B, 00, 3: [4] V. Torra, Aggregato of lgutc label whe ematc baed o atoym, Iteratoal Joural ofitellget Sytem, 00, 6: [5] Z.S. Xu, A method baed o lgutc aggregato operator for group deco makg wth lgutc preferece relato, Iformato Scece, 004, 66: [6] Z.S. Xu, Devato meaure of lgutc preferece relato group deco makg, Omega, 005, 33: [7] Z.S. Xu, Group deco makg baed o multple type of lgutc preferece relato, Iformato Scece, 008, 78: [8] Z.S. Xu, EOWA ad EOWG operator for aggregatg lgutc label baed olgutc preferece relato, Iteratoal Joural of Ucertaty, Fuzze ad Kowledge-Baed Sytem, 004, : [9] M. O Haga, Aggregatg template rule atecedet real-tme expert ytem wth fuzzy et logc, I: Proc d Aual IEEE Alomar Coferece o Sgal, Sytem ad Computer, IEEE ad Maple Pre, Pacfc Grove, CA, 988, pp [0] D.P. Flev ad R.R. Yager, O the ue of obtag OWA operator weght, Fuzzy Set ad Sytem, 998, 94: [] R.R. Yager, OWA aggregato over a cotuou terval argumet wth applcato to deco makg, IEEE Traacto o Sytem, Ma, ad Cyberetc-Part B, 004, 34: [] Z.S. Xu, A overvew of method for determg OWA weght, Iteratoal Joural of Itellget Sytem, 005, 0:

Group Decision Making with Triangular Fuzzy Linguistic Variables

Group Decision Making with Triangular Fuzzy Linguistic Variables roup Deco Makg wth ragular Fuzzy Lgutc Varable Zehu Xu Departmet of Maagemet Scece ad Egeerg School of Ecoomc ad Maagemet ghua Uverty, Beg 0008, Cha Xu_zehu@6.et Abtract. I group deco makg wth lgutc formato,

More information

A LINGUISTIC-VALUED WEIGHTED AGGREGATION OPERATOR TO MULTIPLE ATTRIBUTE GROUP DECISION MAKING WITH QUANTITATIVE AND QUALITATIVE INFORMATION

A LINGUISTIC-VALUED WEIGHTED AGGREGATION OPERATOR TO MULTIPLE ATTRIBUTE GROUP DECISION MAKING WITH QUANTITATIVE AND QUALITATIVE INFORMATION A LINGUISTIC-VALUED WEIGHTED AGGREGATION OPERATOR TO MULTIPLE ATTRIBUTE GROUP DECISION MAKING WITH QUANTITATIVE AND QUALITATIVE INFORMATION XIAOBING LI Itellget Cotrol Developmet Ceter Southwest Jaotog

More information

Linear Approximating to Integer Addition

Linear Approximating to Integer Addition Lear Approxmatg to Iteger Addto L A-Pg Bejg 00085, P.R. Cha apl000@a.com Abtract The teger addto ofte appled cpher a a cryptographc mea. I th paper we wll preet ome reult about the lear approxmatg for

More information

Some Hybrid Geometric Aggregation Operators with 2-tuple Linguistic Information and Their Applications to Multi-attribute Group Decision Making

Some Hybrid Geometric Aggregation Operators with 2-tuple Linguistic Information and Their Applications to Multi-attribute Group Decision Making Iteratoal Joural of Computatoal Itellgece Systems Vol 6 No (July 0 750-76 Some Hybrd Geometrc Aggregato Operators wth -tuple Lgustc Iformato ad her Applcatos to Mult-attrbute Group Decso Mag Shu-Pg Wa

More information

International Journal of Pure and Applied Sciences and Technology

International Journal of Pure and Applied Sciences and Technology It J Pure Appl Sc Techol, () (00), pp 79-86 Iteratoal Joural of Pure ad Appled Scece ad Techology ISSN 9-607 Avalable ole at wwwjopaaat Reearch Paper Some Stroger Chaotc Feature of the Geeralzed Shft Map

More information

Some Aggregation Operators with Intuitionistic Trapezoid Fuzzy Linguistic Information and their Applications to Multi-Attribute Group Decision Making

Some Aggregation Operators with Intuitionistic Trapezoid Fuzzy Linguistic Information and their Applications to Multi-Attribute Group Decision Making Appl. Math. If. Sc. 8 No. 5 2427-2436 (2014) 2427 Appled Mathematcs & Iformato Sceces A Iteratoal Joural http://dx.do.org/10.12785/ams/080538 Some Aggregato Operators wth Itutostc Trapezod Fuzzy Lgustc

More information

Trignometric Inequations and Fuzzy Information Theory

Trignometric Inequations and Fuzzy Information Theory Iteratoal Joural of Scetfc ad Iovatve Mathematcal Reearch (IJSIMR) Volume, Iue, Jauary - 0, PP 00-07 ISSN 7-07X (Prt) & ISSN 7- (Ole) www.arcjoural.org Trgometrc Iequato ad Fuzzy Iformato Theory P.K. Sharma,

More information

Research Article A Fuzzy Multi-attribute Decision Making Method for Sensory Evaluation of Tea Liquor

Research Article A Fuzzy Multi-attribute Decision Making Method for Sensory Evaluation of Tea Liquor Advace Joural of Food Scece ad Techology 9(2: 87-9, 205 DOI: 0.9026/aft.9.99 ISSN: 202-868; e-issn: 202-876 205 Maxwell Scetfc Publcato Corp. Submtted: October 05, 20 Accepted: March 20, 205 Publhed: Augut

More information

Analyzing Fuzzy System Reliability Using Vague Set Theory

Analyzing Fuzzy System Reliability Using Vague Set Theory Iteratoal Joural of Appled Scece ad Egeerg 2003., : 82-88 Aalyzg Fuzzy System Relablty sg Vague Set Theory Shy-Mg Che Departmet of Computer Scece ad Iformato Egeerg, Natoal Tawa versty of Scece ad Techology,

More information

Notes on Distance and Similarity Measures of Dual Hesitant Fuzzy Sets

Notes on Distance and Similarity Measures of Dual Hesitant Fuzzy Sets ING Iteratoal Joural of ppled Mathematc 46:4 IJM_46_4_ Note o Dtace ad Smlarty Meaure of Dual Hetat Fuzzy Set Le Wag Xag Zheg* L Zhag Qag Yue Member ING btract he Dual Hetat Fuzzy Set (DHFS a ueful tool

More information

Reaction Time VS. Drug Percentage Subject Amount of Drug Times % Reaction Time in Seconds 1 Mary John Carl Sara William 5 4

Reaction Time VS. Drug Percentage Subject Amount of Drug Times % Reaction Time in Seconds 1 Mary John Carl Sara William 5 4 CHAPTER Smple Lear Regreo EXAMPLE A expermet volvg fve ubject coducted to determe the relatohp betwee the percetage of a certa drug the bloodtream ad the legth of tme t take the ubject to react to a tmulu.

More information

An Indian Journal FULL PAPER ABSTRACT KEYWORDS. Trade Science Inc. Research on scheme evaluation method of automation mechatronic systems

An Indian Journal FULL PAPER ABSTRACT KEYWORDS. Trade Science Inc. Research on scheme evaluation method of automation mechatronic systems [ype text] [ype text] [ype text] ISSN : 0974-7435 Volume 0 Issue 6 Boechology 204 Ida Joural FULL PPER BIJ, 0(6, 204 [927-9275] Research o scheme evaluato method of automato mechatroc systems BSRC Che

More information

Group decision-making based on heterogeneous preference. relations with self-confidence

Group decision-making based on heterogeneous preference. relations with self-confidence Group decso-mag based o heterogeeous preferece relatos wth self-cofdece Yucheg Dog,Weq Lu, Busess School, Schua Uversty, Chegdu 60065, Cha E-mal: ycdog@scu.edu.c; wqlu@stu.scu.edu.c Fracsco Chclaa, Faculty

More information

Generalization of the Dissimilarity Measure of Fuzzy Sets

Generalization of the Dissimilarity Measure of Fuzzy Sets Iteratoal Mathematcal Forum 2 2007 o. 68 3395-3400 Geeralzato of the Dssmlarty Measure of Fuzzy Sets Faramarz Faghh Boformatcs Laboratory Naobotechology Research Ceter vesa Research Isttute CECR Tehra

More information

A Result of Convergence about Weighted Sum for Exchangeable Random Variable Sequence in the Errors-in-Variables Model

A Result of Convergence about Weighted Sum for Exchangeable Random Variable Sequence in the Errors-in-Variables Model AMSE JOURNALS-AMSE IIETA publcato-17-sere: Advace A; Vol. 54; N ; pp 3-33 Submtted Mar. 31, 17; Reved Ju. 11, 17, Accepted Ju. 18, 17 A Reult of Covergece about Weghted Sum for Exchageable Radom Varable

More information

On a Truncated Erlang Queuing System. with Bulk Arrivals, Balking and Reneging

On a Truncated Erlang Queuing System. with Bulk Arrivals, Balking and Reneging Appled Mathematcal Scece Vol. 3 9 o. 3 3-3 O a Trucated Erlag Queug Sytem wth Bul Arrval Balg ad Reegg M. S. El-aoumy ad M. M. Imal Departmet of Stattc Faculty Of ommerce Al- Azhar Uverty. Grl Brach Egypt

More information

Some geometric aggregation operators based on log-normally distributed random variables

Some geometric aggregation operators based on log-normally distributed random variables Iteratoal Joural of Computatoal Itellgece Systems, Vol. 7, o. 6 (December 04, 096-08 Some geometrc aggregato operators based o log-ormally dstrbuted radom varables -Fa Wag School of Scece, Hua Uversty

More information

Simple Linear Regression Analysis

Simple Linear Regression Analysis LINEAR REGREION ANALYSIS MODULE II Lecture - 5 Smple Lear Regreo Aaly Dr Shalabh Departmet of Mathematc Stattc Ida Ittute of Techology Kapur Jot cofdece rego for A jot cofdece rego for ca alo be foud Such

More information

Fuzzy Number Intuitionistic Fuzzy Arithmetic Aggregation Operators

Fuzzy Number Intuitionistic Fuzzy Arithmetic Aggregation Operators 04 Iteratoal Joural of Fuzzy Systems Vol. 0 No. Jue 008 Fuzzy Number Itutostc Fuzzy rthmetc ggregato Operators Xfa Wag bstract fuzzy umber tutostc fuzzy set (FNIFS s a geeralzato of tutostc fuzzy set.

More information

Some q-rung orthopair linguistic Heronian mean operators with their application to multi-attribute group decision making

Some q-rung orthopair linguistic Heronian mean operators with their application to multi-attribute group decision making 10.445/acs.018.15483 Archves of Cotrol Sceces Volume 8LXIV) 018 No. 4 pages 551 583 Some q-rug orthopar lgustc Heroa mea operators wth ther applcato to mult-attrbute group decso makg LI LI RUNTONG ZHANG

More information

Ranking Bank Branches with Interval Data By IAHP and TOPSIS

Ranking Bank Branches with Interval Data By IAHP and TOPSIS Rag Ba Braches wth terval Data By HP ad TPSS Tayebeh Rezaetazaa Departmet of Mathematcs, slamc zad Uversty, Badar bbas Brach, Badar bbas, ra Mahaz Barhordarahmad Departmet of Mathematcs, slamc zad Uversty,

More information

The uncertain probabilistic weighted average and its application in the theory of expertons

The uncertain probabilistic weighted average and its application in the theory of expertons Afrca Joural of Busess Maagemet Vol. 5(15), pp. 6092-6102, 4 August, 2011 Avalable ole at http://www.academcjourals.org/ajbm ISSN 1993-8233 2011 Academc Jourals Full Legth Research Paper The ucerta probablstc

More information

TWO NEW WEIGHTED MEASURES OF FUZZY ENTROPY AND THEIR PROPERTIES

TWO NEW WEIGHTED MEASURES OF FUZZY ENTROPY AND THEIR PROPERTIES merca. Jr. of Mathematcs ad Sceces Vol., No.,(Jauary 0) Copyrght Md Reader Publcatos www.jouralshub.com TWO NEW WEIGTED MESURES OF FUZZY ENTROPY ND TEIR PROPERTIES R.K.Tul Departmet of Mathematcs S.S.M.

More information

Functions of Random Variables

Functions of Random Variables Fuctos of Radom Varables Chapter Fve Fuctos of Radom Varables 5. Itroducto A geeral egeerg aalyss model s show Fg. 5.. The model output (respose) cotas the performaces of a system or product, such as weght,

More information

FUZZY MULTI-CRITERIA APPROACH TO ORDERING POLICY RANKING IN A SUPPLY CHAIN

FUZZY MULTI-CRITERIA APPROACH TO ORDERING POLICY RANKING IN A SUPPLY CHAIN Yugolav Joural of Operato Reearch 5 (2005), Number 2, 243-258 FUZZY MULTI-CRITERIA APPROACH TO ORDERING POLICY RANKING IN A SUPPLY CHAIN Dajela TADIĆ Faculty of Mechacal Egeerg, Uverty of Kragujevac Kragujevac,

More information

European Journal of Mathematics and Computer Science Vol. 5 No. 2, 2018 ISSN

European Journal of Mathematics and Computer Science Vol. 5 No. 2, 2018 ISSN Europea Joural of Mathematc ad Computer Scece Vol. 5 o., 018 ISS 059-9951 APPLICATIO OF ASYMPTOTIC DISTRIBUTIO OF MA-HITEY STATISTIC TO DETERMIE THE DIFFERECE BETEE THE SYSTOLIC BLOOD PRESSURE OF ME AD

More information

MEASURES OF DISPERSION

MEASURES OF DISPERSION MEASURES OF DISPERSION Measure of Cetral Tedecy: Measures of Cetral Tedecy ad Dsperso ) Mathematcal Average: a) Arthmetc mea (A.M.) b) Geometrc mea (G.M.) c) Harmoc mea (H.M.) ) Averages of Posto: a) Meda

More information

Ordinary Least Squares Regression. Simple Regression. Algebra and Assumptions.

Ordinary Least Squares Regression. Simple Regression. Algebra and Assumptions. Ordary Least Squares egresso. Smple egresso. Algebra ad Assumptos. I ths part of the course we are gog to study a techque for aalysg the lear relatoshp betwee two varables Y ad X. We have pars of observatos

More information

Probabilistic Linguistic Power Aggregation Operators for Multi-Criteria Group Decision Making

Probabilistic Linguistic Power Aggregation Operators for Multi-Criteria Group Decision Making Artcle Probablstc Lgustc Power Aggregato Operators for Mult-Crtera Group Decso Makg Agbodah Koba 1,2 ID, Decu Lag 1,2, * ad X He 1 1 School of Maagemet ad Ecoomcs, Uversty of Electroc Scece ad Techology

More information

COMPROMISE HYPERSPHERE FOR STOCHASTIC DOMINANCE MODEL

COMPROMISE HYPERSPHERE FOR STOCHASTIC DOMINANCE MODEL Sebasta Starz COMPROMISE HYPERSPHERE FOR STOCHASTIC DOMINANCE MODEL Abstract The am of the work s to preset a method of rakg a fte set of dscrete radom varables. The proposed method s based o two approaches:

More information

Median as a Weighted Arithmetic Mean of All Sample Observations

Median as a Weighted Arithmetic Mean of All Sample Observations Meda as a Weghted Arthmetc Mea of All Sample Observatos SK Mshra Dept. of Ecoomcs NEHU, Shllog (Ida). Itroducto: Iumerably may textbooks Statstcs explctly meto that oe of the weakesses (or propertes) of

More information

REVIEW OF SIMPLE LINEAR REGRESSION SIMPLE LINEAR REGRESSION

REVIEW OF SIMPLE LINEAR REGRESSION SIMPLE LINEAR REGRESSION REVIEW OF SIMPLE LINEAR REGRESSION SIMPLE LINEAR REGRESSION I lear regreo, we coder the frequecy dtrbuto of oe varable (Y) at each of everal level of a ecod varable (X). Y kow a the depedet varable. The

More information

Multiple Attribute Group Decision Making with Linguistic Information Based on Linguistic Prioritized Operators

Multiple Attribute Group Decision Making with Linguistic Information Based on Linguistic Prioritized Operators Joural of Setf Reearh & Report (): - 0; Artle ojsrr ISSN: 0-0 SCIENCEDOMAIN teratoal wwweedomaorg Multple Attrbute Group Deo Makg wth gut Iformato Baed o gut Prortzed Operator Zhmg Zhag * College of Mathemat

More information

Third handout: On the Gini Index

Third handout: On the Gini Index Thrd hadout: O the dex Corrado, a tala statstca, proposed (, 9, 96) to measure absolute equalt va the mea dfferece whch s defed as ( / ) where refers to the total umber of dvduals socet. Assume that. The

More information

Solving Constrained Flow-Shop Scheduling. Problems with Three Machines

Solving Constrained Flow-Shop Scheduling. Problems with Three Machines It J Cotemp Math Sceces, Vol 5, 2010, o 19, 921-929 Solvg Costraed Flow-Shop Schedulg Problems wth Three Maches P Pada ad P Rajedra Departmet of Mathematcs, School of Advaced Sceces, VIT Uversty, Vellore-632

More information

CS473-Algorithms I. Lecture 12b. Dynamic Tables. CS 473 Lecture X 1

CS473-Algorithms I. Lecture 12b. Dynamic Tables. CS 473 Lecture X 1 CS473-Algorthm I Lecture b Dyamc Table CS 473 Lecture X Why Dyamc Table? I ome applcato: We do't kow how may object wll be tored a table. We may allocate pace for a table But, later we may fd out that

More information

Distance and Similarity Measures for Intuitionistic Hesitant Fuzzy Sets

Distance and Similarity Measures for Intuitionistic Hesitant Fuzzy Sets Iteratoal Coferece o Artfcal Itellgece: Techologes ad Applcatos (ICAITA 206) Dstace ad Smlarty Measures for Itutostc Hestat Fuzzy Sets Xumg Che,2*, Jgmg L,2, L Qa ad Xade Hu School of Iformato Egeerg,

More information

Multi Objective Fuzzy Inventory Model with. Demand Dependent Unit Cost and Lead Time. Constraints A Karush Kuhn Tucker Conditions.

Multi Objective Fuzzy Inventory Model with. Demand Dependent Unit Cost and Lead Time. Constraints A Karush Kuhn Tucker Conditions. It. Joural of Math. Aalyss, Vol. 8, 204, o. 4, 87-93 HIKARI Ltd, www.m-hkar.com http://dx.do.org/0.2988/jma.204.30252 Mult Objectve Fuzzy Ivetory Model wth Demad Depedet Ut Cost ad Lead Tme Costrats A

More information

Estimation of Stress- Strength Reliability model using finite mixture of exponential distributions

Estimation of Stress- Strength Reliability model using finite mixture of exponential distributions Iteratoal Joural of Computatoal Egeerg Research Vol, 0 Issue, Estmato of Stress- Stregth Relablty model usg fte mxture of expoetal dstrbutos K.Sadhya, T.S.Umamaheswar Departmet of Mathematcs, Lal Bhadur

More information

ROOT-LOCUS ANALYSIS. Lecture 11: Root Locus Plot. Consider a general feedback control system with a variable gain K. Y ( s ) ( ) K

ROOT-LOCUS ANALYSIS. Lecture 11: Root Locus Plot. Consider a general feedback control system with a variable gain K. Y ( s ) ( ) K ROOT-LOCUS ANALYSIS Coder a geeral feedback cotrol yte wth a varable ga. R( Y( G( + H( Root-Locu a plot of the loc of the pole of the cloed-loop trafer fucto whe oe of the yte paraeter ( vared. Root locu

More information

Collapsing to Sample and Remainder Means. Ed Stanek. In order to collapse the expanded random variables to weighted sample and remainder

Collapsing to Sample and Remainder Means. Ed Stanek. In order to collapse the expanded random variables to weighted sample and remainder Collapg to Saple ad Reader Mea Ed Staek Collapg to Saple ad Reader Average order to collape the expaded rado varable to weghted aple ad reader average, we pre-ultpled by ( M C C ( ( M C ( M M M ( M M M,

More information

Comparing Different Estimators of three Parameters for Transmuted Weibull Distribution

Comparing Different Estimators of three Parameters for Transmuted Weibull Distribution Global Joural of Pure ad Appled Mathematcs. ISSN 0973-768 Volume 3, Number 9 (207), pp. 55-528 Research Ida Publcatos http://www.rpublcato.com Comparg Dfferet Estmators of three Parameters for Trasmuted

More information

Generalized Convex Functions on Fractal Sets and Two Related Inequalities

Generalized Convex Functions on Fractal Sets and Two Related Inequalities Geeralzed Covex Fuctos o Fractal Sets ad Two Related Iequaltes Huxa Mo, X Su ad Dogya Yu 3,,3School of Scece, Bejg Uversty of Posts ad Telecommucatos, Bejg,00876, Cha, Correspodece should be addressed

More information

Scheduling Jobs with a Common Due Date via Cooperative Game Theory

Scheduling Jobs with a Common Due Date via Cooperative Game Theory Amerca Joural of Operato Reearch, 203, 3, 439-443 http://dx.do.org/0.4236/ajor.203.35042 Publhed Ole eptember 203 (http://www.crp.org/joural/ajor) chedulg Job wth a Commo Due Date va Cooperatve Game Theory

More information

Journal of Mathematical Analysis and Applications

Journal of Mathematical Analysis and Applications J. Math. Aal. Appl. 365 200) 358 362 Cotets lsts avalable at SceceDrect Joural of Mathematcal Aalyss ad Applcatos www.elsever.com/locate/maa Asymptotc behavor of termedate pots the dfferetal mea value

More information

European Journal of Mathematics and Computer Science Vol. 5 No. 2, 2018 ISSN

European Journal of Mathematics and Computer Science Vol. 5 No. 2, 2018 ISSN Europea Joural of Mathematc ad Computer Scece Vol. 5 o., 018 ISS 059-9951 APPLICATIO OF ASYMPTOTIC DISTRIBUTIO OF MA-HITEY STATISTIC TO DETERMIE THE DIFFERECE BETEE THE SYSTOLIC BLOOD PRESSURE OF ME AD

More information

Basic Structures: Sets, Functions, Sequences, and Sums

Basic Structures: Sets, Functions, Sequences, and Sums ac Structure: Set, Fucto, Sequece, ad Sum CSC-9 Dcrete Structure Kotat uch - LSU Set et a uordered collecto o object Eglh alphabet vowel: V { a, e,, o, u} a V b V Odd potve teger le tha : elemet o et member

More information

Summary of the lecture in Biostatistics

Summary of the lecture in Biostatistics Summary of the lecture Bostatstcs Probablty Desty Fucto For a cotuos radom varable, a probablty desty fucto s a fucto such that: 0 dx a b) b a dx A probablty desty fucto provdes a smple descrpto of the

More information

Research Article Linguistic Intuitionistic Fuzzy Sets and Application in MAGDM

Research Article Linguistic Intuitionistic Fuzzy Sets and Application in MAGDM Hdaw Publshg Corporato Joural of Appled Mathematcs, Artcle ID 432092, 11 pages http://dx.do.org/10.1155/2014/432092 Research Artcle Lgustc Itutostc Fuzzy Sets ad Applcato MAGDM Hum Zhag School of Maagemet,

More information

Bayes Estimator for Exponential Distribution with Extension of Jeffery Prior Information

Bayes Estimator for Exponential Distribution with Extension of Jeffery Prior Information Malaysa Joural of Mathematcal Sceces (): 97- (9) Bayes Estmator for Expoetal Dstrbuto wth Exteso of Jeffery Pror Iformato Hadeel Salm Al-Kutub ad Noor Akma Ibrahm Isttute for Mathematcal Research, Uverst

More information

A New Measure of Probabilistic Entropy. and its Properties

A New Measure of Probabilistic Entropy. and its Properties Appled Mathematcal Sceces, Vol. 4, 200, o. 28, 387-394 A New Measure of Probablstc Etropy ad ts Propertes Rajeesh Kumar Departmet of Mathematcs Kurukshetra Uversty Kurukshetra, Ida rajeesh_kuk@redffmal.com

More information

Some Notes on the Probability Space of Statistical Surveys

Some Notes on the Probability Space of Statistical Surveys Metodološk zvezk, Vol. 7, No., 200, 7-2 ome Notes o the Probablty pace of tatstcal urveys George Petrakos Abstract Ths paper troduces a formal presetato of samplg process usg prcples ad cocepts from Probablty

More information

On the energy of complement of regular line graphs

On the energy of complement of regular line graphs MATCH Coucato Matheatcal ad Coputer Chetry MATCH Cou Math Coput Che 60 008) 47-434 ISSN 0340-653 O the eergy of copleet of regular le graph Fateeh Alaghpour a, Baha Ahad b a Uverty of Tehra, Tehra, Ira

More information

Modified Cosine Similarity Measure between Intuitionistic Fuzzy Sets

Modified Cosine Similarity Measure between Intuitionistic Fuzzy Sets Modfed ose mlarty Measure betwee Itutostc Fuzzy ets hao-mg wag ad M-he Yag,* Deartmet of led Mathematcs, hese ulture Uversty, Tae, Tawa Deartmet of led Mathematcs, hug Yua hrsta Uversty, hug-l, Tawa msyag@math.cycu.edu.tw

More information

Some Wgh Inequalities for Univalent Harmonic Analytic Functions

Some Wgh Inequalities for Univalent Harmonic Analytic Functions ppled Mathematc 464-469 do:436/am66 Publhed Ole December (http://wwwscrporg/joural/am Some Wgh Ieualte for Uvalet Harmoc alytc Fucto btract Pooam Sharma Departmet of Mathematc ad troomy Uverty of Lucow

More information

Nargozy T. Danayev*, Darkhan Zh. Akhmed-Zaki* THE USAGE OF MATHEMATICAL MLT MODEL FOR THE CALCULATION OF THERMAL FILTRATION

Nargozy T. Danayev*, Darkhan Zh. Akhmed-Zaki* THE USAGE OF MATHEMATICAL MLT MODEL FOR THE CALCULATION OF THERMAL FILTRATION WIERTNICTWO NAFTA GAZ TOM 3/ 6 Nargozy T. Daayev*, Darka Z. Akmed-Zak* THE USAGE OF MATHEMATICAL MLT MODEL FOR THE CALCULATION OF THERMAL FILTRATION Durg te reearc we ued a well-kow matematcal MLT model

More information

Research Article A New Iterative Method for Common Fixed Points of a Finite Family of Nonexpansive Mappings

Research Article A New Iterative Method for Common Fixed Points of a Finite Family of Nonexpansive Mappings Hdaw Publshg Corporato Iteratoal Joural of Mathematcs ad Mathematcal Sceces Volume 009, Artcle ID 391839, 9 pages do:10.1155/009/391839 Research Artcle A New Iteratve Method for Commo Fxed Pots of a Fte

More information

INEQUALITIES USING CONVEX COMBINATION CENTERS AND SET BARYCENTERS

INEQUALITIES USING CONVEX COMBINATION CENTERS AND SET BARYCENTERS Joural of Mathematcal Scece: Advace ad Alcato Volume 24, 23, Page 29-46 INEQUALITIES USING CONVEX COMBINATION CENTERS AND SET BARYCENTERS ZLATKO PAVIĆ Mechacal Egeerg Faculty Slavok Brod Uverty of Ojek

More information

It is Advantageous to Make a Syllabus as Precise as Possible: Decision-Theoretic Analysis

It is Advantageous to Make a Syllabus as Precise as Possible: Decision-Theoretic Analysis Joural of Iovatve Techology ad Educato, Vol. 4, 2017, o. 1, 1-5 HIKARI Ltd, www.m-hkar.com https://do.org/10.12988/jte.2017.61146 It s Advatageous to Make a Syllabus as Precse as Possble: Decso-Theoretc

More information

Research Article Interval-Valued Intuitionistic Fuzzy Ordered Weighted Cosine Similarity Measure and Its Application in Investment Decision-Making

Research Article Interval-Valued Intuitionistic Fuzzy Ordered Weighted Cosine Similarity Measure and Its Application in Investment Decision-Making Hdaw Complexty Volume 2017 Artcle ID 1891923 11 pages https://do.org/10.1155/2017/1891923 Research Artcle Iterval-Valued Itutostc Fuzzy Ordered Weghted Cose Smlarty Measure ad Its Applcato Ivestmet Decso-Makg

More information

Chapter 5 Properties of a Random Sample

Chapter 5 Properties of a Random Sample Lecture 6 o BST 63: Statstcal Theory I Ku Zhag, /0/008 Revew for the prevous lecture Cocepts: t-dstrbuto, F-dstrbuto Theorems: Dstrbutos of sample mea ad sample varace, relatoshp betwee sample mea ad sample

More information

CIS 800/002 The Algorithmic Foundations of Data Privacy October 13, Lecture 9. Database Update Algorithms: Multiplicative Weights

CIS 800/002 The Algorithmic Foundations of Data Privacy October 13, Lecture 9. Database Update Algorithms: Multiplicative Weights CIS 800/002 The Algorthmc Foudatos of Data Prvacy October 13, 2011 Lecturer: Aaro Roth Lecture 9 Scrbe: Aaro Roth Database Update Algorthms: Multplcatve Weghts We ll recall aga) some deftos from last tme:

More information

The Primitive Idempotents in

The Primitive Idempotents in Iteratoal Joural of Algebra, Vol, 00, o 5, 3 - The Prmtve Idempotets FC - I Kulvr gh Departmet of Mathematcs, H College r Jwa Nagar (rsa)-5075, Ida kulvrsheora@yahoocom K Arora Departmet of Mathematcs,

More information

Strong Convergence of Weighted Averaged Approximants of Asymptotically Nonexpansive Mappings in Banach Spaces without Uniform Convexity

Strong Convergence of Weighted Averaged Approximants of Asymptotically Nonexpansive Mappings in Banach Spaces without Uniform Convexity BULLETIN of the MALAYSIAN MATHEMATICAL SCIENCES SOCIETY Bull. Malays. Math. Sc. Soc. () 7 (004), 5 35 Strog Covergece of Weghted Averaged Appromats of Asymptotcally Noepasve Mappgs Baach Spaces wthout

More information

1 Mixed Quantum State. 2 Density Matrix. CS Density Matrices, von Neumann Entropy 3/7/07 Spring 2007 Lecture 13. ψ = α x x. ρ = p i ψ i ψ i.

1 Mixed Quantum State. 2 Density Matrix. CS Density Matrices, von Neumann Entropy 3/7/07 Spring 2007 Lecture 13. ψ = α x x. ρ = p i ψ i ψ i. CS 94- Desty Matrces, vo Neuma Etropy 3/7/07 Sprg 007 Lecture 3 I ths lecture, we wll dscuss the bascs of quatum formato theory I partcular, we wll dscuss mxed quatum states, desty matrces, vo Neuma etropy

More information

Analysis of Lagrange Interpolation Formula

Analysis of Lagrange Interpolation Formula P IJISET - Iteratoal Joural of Iovatve Scece, Egeerg & Techology, Vol. Issue, December 4. www.jset.com ISS 348 7968 Aalyss of Lagrage Iterpolato Formula Vjay Dahya PDepartmet of MathematcsMaharaja Surajmal

More information

Management Science Letters

Management Science Letters Maagemet Scece Letters 2 (202) 29 42 Cotets lsts avalable at GrowgScece Maagemet Scece Letters homepage: www.growgscece.com/msl A goal programmg method for dervg fuzzy prortes of crtera from cosstet fuzzy

More information

Fuzzy TOPSIS Based on α Level Set for Academic Staff Selection

Fuzzy TOPSIS Based on α Level Set for Academic Staff Selection Gadg Busess ad Maagemet Joural Vol. No., 57-70, 007 Fuzzy TOPSIS Based o evel Set for Academc Staff Selecto Nazrah Raml Nor Azzah M. Yacob Faculty of Iformato Techology ad Quattatve Scece Uverst Tekolog

More information

Multiple Attribute Decision Making Based on Interval Number Aggregation Operators Hui LI* and Bing-jiang ZHANG

Multiple Attribute Decision Making Based on Interval Number Aggregation Operators Hui LI* and Bing-jiang ZHANG 206 Iteratoal Coferece o Power, Eergy Egeerg ad Maageet (PEEM 206) ISBN: 978--60595-324-3 Multple Attrbute Decso Makg Based o Iterval Nuber Aggregato Operators Hu LI* ad Bg-jag ZHANG School of Appled Scece,

More information

best estimate (mean) for X uncertainty or error in the measurement (systematic, random or statistical) best

best estimate (mean) for X uncertainty or error in the measurement (systematic, random or statistical) best Error Aalyss Preamble Wheever a measuremet s made, the result followg from that measuremet s always subject to ucertaty The ucertaty ca be reduced by makg several measuremets of the same quatty or by mprovg

More information

Reliability and Cost Analysis of a Series System Model Using Fuzzy Parametric Geometric Programming

Reliability and Cost Analysis of a Series System Model Using Fuzzy Parametric Geometric Programming P P P IJISET - Iteratoal Joural of Iovatve Scece, Egeerg & Techology, Vol. Iue 8, October 204. Relablty ad Cot Aaly of a Sere Syte Model Ug Fuzzy Paraetrc Geoetrc Prograg Medhat El-Dacee P 2 2 P, Fahee

More information

MAX-MIN AND MIN-MAX VALUES OF VARIOUS MEASURES OF FUZZY DIVERGENCE

MAX-MIN AND MIN-MAX VALUES OF VARIOUS MEASURES OF FUZZY DIVERGENCE merca Jr of Mathematcs ad Sceces Vol, No,(Jauary 0) Copyrght Md Reader Publcatos wwwjouralshubcom MX-MIN ND MIN-MX VLUES OF VRIOUS MESURES OF FUZZY DIVERGENCE RKTul Departmet of Mathematcs SSM College

More information

COMPARISON OF ANALYTIC HIERARCHY PROCESS AND SOME NEW OPTIMIZATION PROCEDURES FOR RATIO SCALING

COMPARISON OF ANALYTIC HIERARCHY PROCESS AND SOME NEW OPTIMIZATION PROCEDURES FOR RATIO SCALING Please cte ths artcle as: Paweł Kazbudzk, Comparso of aalytc herarchy process ad some ew optmzato procedures for rato scalg, Scetfc Research of the Isttute of Mathematcs ad Computer Scece, 0, Volume 0,

More information

T-DOF PID Controller Design using Characteristic Ratio Assignment Method for Quadruple Tank Process

T-DOF PID Controller Design using Characteristic Ratio Assignment Method for Quadruple Tank Process World Academy of Scece, Egeerg ad Techology Iteratoal Joural of Electrcal ad Iformato Egeerg Vol:, No:, 7 T-DOF PID Cotroller Deg ug Charactertc Rato Agmet Method for Quadruple Tak Proce Tacha Sukr, U-tha

More information

Termination Analysis of Programs with Periodic Orbit on the Boundary

Termination Analysis of Programs with Periodic Orbit on the Boundary Iteratoal Coferece o Itellget Sytem Reearch ad Mechatroc Egeerg (ISRME 5) Termato Aaly of Program wth Perodc Orbt o the Boudary Jgm Che, a, Y L*, b, Guag Zhu, c, Chuaca L, d, Fagja Huag 3, e School of

More information

On L- Fuzzy Sets. T. Rama Rao, Ch. Prabhakara Rao, Dawit Solomon And Derso Abeje.

On L- Fuzzy Sets. T. Rama Rao, Ch. Prabhakara Rao, Dawit Solomon And Derso Abeje. Iteratoal Joural of Fuzzy Mathematcs ad Systems. ISSN 2248-9940 Volume 3, Number 5 (2013), pp. 375-379 Research Ida Publcatos http://www.rpublcato.com O L- Fuzzy Sets T. Rama Rao, Ch. Prabhakara Rao, Dawt

More information

A New Approach to Multi-spaces Through the Application

A New Approach to Multi-spaces Through the Application Neutrosophc Sets ad Systems Vol 7 015 34 A New Approach to Mult-spaces Through the Applcato Mumtaz Al 1 Floret Smaradache Sad Broum 3 ad Muhammad Shabr 4 14 Departmet of Mathematcs Quad--Azam Uversty Islamabad

More information

PICTURE FUZZY CROSS-ENTROPY FOR MULTIPLE ATTRIBUTE DECISION MAKING PROBLEMS

PICTURE FUZZY CROSS-ENTROPY FOR MULTIPLE ATTRIBUTE DECISION MAKING PROBLEMS Joural of Busess Ecoomcs ad Maagemet ISSN 6-699 / eissn 2029-4433 206 Volume 7(4): 49 502 do:0.3846/6699.206.9747 PICTURE FUZZY CROSS-ENTROPY FOR MULTIPLE ATTRIBUTE DECISION MAKING PROBLEMS Guwu WEI School

More information

Point Estimation: definition of estimators

Point Estimation: definition of estimators Pot Estmato: defto of estmators Pot estmator: ay fucto W (X,..., X ) of a data sample. The exercse of pot estmato s to use partcular fuctos of the data order to estmate certa ukow populato parameters.

More information

IRREDUCIBLE COVARIANT REPRESENTATIONS ASSOCIATED TO AN R-DISCRETE GROUPOID

IRREDUCIBLE COVARIANT REPRESENTATIONS ASSOCIATED TO AN R-DISCRETE GROUPOID UPB Sc Bull Sere A Vol 69 No 7 ISSN 3-77 IRREDUCIBLE COVARIANT REPRESENTATIONS ASSOCIATED TO AN R-DISCRETE GROUPOID Roxaa VIDICAN Ue perech covarate poztv defte ( T ) relatv la u grupod r-dcret G e poate

More information

Chapter 4 Multiple Random Variables

Chapter 4 Multiple Random Variables Revew for the prevous lecture: Theorems ad Examples: How to obta the pmf (pdf) of U = g (, Y) ad V = g (, Y) Chapter 4 Multple Radom Varables Chapter 44 Herarchcal Models ad Mxture Dstrbutos Examples:

More information

ANOVA with Summary Statistics: A STATA Macro

ANOVA with Summary Statistics: A STATA Macro ANOVA wth Summary Stattc: A STATA Macro Nadeem Shafque Butt Departmet of Socal ad Prevetve Pedatrc Kg Edward Medcal College, Lahore, Pata Shahd Kamal Ittute of Stattc, Uverty of the Puab Lahore, Pata Muhammad

More information

A note on testing the covariance matrix for large dimension

A note on testing the covariance matrix for large dimension A ote o tetg the covarace matrx for large dmeo Melae Brke Ruhr-Uvertät Bochum Fakultät für Mathematk 44780 Bochum, Germay e-mal: melae.brke@ruhr-u-bochum.de Holger ette Ruhr-Uvertät Bochum Fakultät für

More information

10.2 Series. , we get. which is called an infinite series ( or just a series) and is denoted, for short, by the symbol. i i n

10.2 Series. , we get. which is called an infinite series ( or just a series) and is denoted, for short, by the symbol. i i n 0. Sere I th ecto, we wll troduce ere tht wll be dcug for the ret of th chpter. Wht ere? If we dd ll term of equece, we get whch clled fte ere ( or jut ere) d deoted, for hort, by the ymbol or Doe t mke

More information

PROJECTION PROBLEM FOR REGULAR POLYGONS

PROJECTION PROBLEM FOR REGULAR POLYGONS Joural of Mathematcal Sceces: Advaces ad Applcatos Volume, Number, 008, Pages 95-50 PROJECTION PROBLEM FOR REGULAR POLYGONS College of Scece Bejg Forestry Uversty Bejg 0008 P. R. Cha e-mal: sl@bjfu.edu.c

More information

Johns Hopkins University Department of Biostatistics Math Review for Introductory Courses

Johns Hopkins University Department of Biostatistics Math Review for Introductory Courses Johs Hopks Uverst Departmet of Bostatstcs Math Revew for Itroductor Courses Ratoale Bostatstcs courses wll rel o some fudametal mathematcal relatoshps, fuctos ad otato. The purpose of ths Math Revew s

More information

Chapter 8: Statistical Analysis of Simulated Data

Chapter 8: Statistical Analysis of Simulated Data Marquette Uversty MSCS600 Chapter 8: Statstcal Aalyss of Smulated Data Dael B. Rowe, Ph.D. Departmet of Mathematcs, Statstcs, ad Computer Scece Copyrght 08 by Marquette Uversty MSCS600 Ageda 8. The Sample

More information

A New Method for Decision Making Based on Soft Matrix Theory

A New Method for Decision Making Based on Soft Matrix Theory Joural of Scetfc esearch & eports 3(5): 0-7, 04; rtcle o. JS.04.5.00 SCIENCEDOMIN teratoal www.scecedoma.org New Method for Decso Mag Based o Soft Matrx Theory Zhmg Zhag * College of Mathematcs ad Computer

More information

CHAPTER VI Statistical Analysis of Experimental Data

CHAPTER VI Statistical Analysis of Experimental Data Chapter VI Statstcal Aalyss of Expermetal Data CHAPTER VI Statstcal Aalyss of Expermetal Data Measuremets do ot lead to a uque value. Ths s a result of the multtude of errors (maly radom errors) that ca

More information

Min-Max Goal Programming Approach For Solving Multi-Objective De Novo Programming Problems

Min-Max Goal Programming Approach For Solving Multi-Objective De Novo Programming Problems Iteratoal Joural of OperatoReearch Iteratoal Joural of Operato ReearchVol. 0, No., 9 99 (0) M-Max Goal Programmg Approach For Solvg Mult-Objectve De Novo Programmg Problem Nurullah Umaruma Uverty of Aaray,

More information

Dice Similarity Measure between Single Valued Neutrosophic Multisets and Its Application in Medical. Diagnosis

Dice Similarity Measure between Single Valued Neutrosophic Multisets and Its Application in Medical. Diagnosis Neutrosophc Sets ad Systems, Vol. 6, 04 48 Dce Smlarty Measure betwee Sgle Valued Neutrosophc Multsets ad ts pplcato Medcal Dagoss Sha Ye ad Ju Ye Tasha Commuty Health Servce Ceter. 9 Hur rdge, Yuecheg

More information

The Necessarily Efficient Point Method for Interval Molp Problems

The Necessarily Efficient Point Method for Interval Molp Problems ISS 6-69 Eglad K Joural of Iformato ad omputg Scece Vol. o. 9 pp. - The ecessarly Effcet Pot Method for Iterval Molp Problems Hassa Mshmast eh ad Marzeh Alezhad + Mathematcs Departmet versty of Ssta ad

More information

GENERATE FUZZY CONCEPTS BASED ON JOIN-IRREDUCIBLE ELEMENTS

GENERATE FUZZY CONCEPTS BASED ON JOIN-IRREDUCIBLE ELEMENTS GENERATE FUZZY CONCEPTS BASED ON JOIN-IRREDUCIBLE ELEMENTS Hua Mao ad *Zhe Zheg Departmet of Mathematcs ad Iformato Scece Hebe Uversty Baodg 071002 Cha *Author for Correspodece: 373380431@qq.com ABSTRACT

More information

f f... f 1 n n (ii) Median : It is the value of the middle-most observation(s).

f f... f 1 n n (ii) Median : It is the value of the middle-most observation(s). CHAPTER STATISTICS Pots to Remember :. Facts or fgures, collected wth a defte pupose, are called Data.. Statstcs s the area of study dealg wth the collecto, presetato, aalyss ad terpretato of data.. The

More information

Bayes (Naïve or not) Classifiers: Generative Approach

Bayes (Naïve or not) Classifiers: Generative Approach Logstc regresso Bayes (Naïve or ot) Classfers: Geeratve Approach What do we mea by Geeratve approach: Lear p(y), p(x y) ad the apply bayes rule to compute p(y x) for makg predctos Ths s essetally makg

More information

Some Distance Measures of Single Valued Neutrosophic Hesitant Fuzzy Sets and Their Applications to Multiple Attribute Decision Making

Some Distance Measures of Single Valued Neutrosophic Hesitant Fuzzy Sets and Their Applications to Multiple Attribute Decision Making ew Treds eutrosophc Theory ad pplcatos PR ISWS, SURPTI PRMIK *, IHS C. GIRI 3 epartmet of Mathematcs, Jadavpur Uversty, Kolkata, 70003, Ida. E-mal: paldam00@gmal.com *epartmet of Mathematcs, adalal Ghosh.T.

More information

Mean is only appropriate for interval or ratio scales, not ordinal or nominal.

Mean is only appropriate for interval or ratio scales, not ordinal or nominal. Mea Same as ordary average Sum all the data values ad dvde by the sample sze. x = ( x + x +... + x Usg summato otato, we wrte ths as x = x = x = = ) x Mea s oly approprate for terval or rato scales, ot

More information

Statistics Descriptive and Inferential Statistics. Instructor: Daisuke Nagakura

Statistics Descriptive and Inferential Statistics. Instructor: Daisuke Nagakura Statstcs Descrptve ad Iferetal Statstcs Istructor: Dasuke Nagakura (agakura@z7.keo.jp) 1 Today s topc Today, I talk about two categores of statstcal aalyses, descrptve statstcs ad feretal statstcs, ad

More information

X ε ) = 0, or equivalently, lim

X ε ) = 0, or equivalently, lim Revew for the prevous lecture Cocepts: order statstcs Theorems: Dstrbutos of order statstcs Examples: How to get the dstrbuto of order statstcs Chapter 5 Propertes of a Radom Sample Secto 55 Covergece

More information

CHARACTERIZATION OF SOFT COMPACT SPACES BASED ON SOFT FILTER

CHARACTERIZATION OF SOFT COMPACT SPACES BASED ON SOFT FILTER CHRCTERIZTION O SOT COMPCT SPCES BSED ON SOT ILTER 1,2 PEI WNG, 1 JILI HE 1 Departmet of Mathematcs ad Iformato Scece, Yul Normal versty, Yul, Guagx, 537000, PRCha 2 School of Mathematcs ad Iformato Scece;

More information