An Indian Journal FULL PAPER ABSTRACT KEYWORDS. Trade Science Inc.

Transcription

1 [Type text] [Type text] [Type text] ISSN : Volume 10 Issue 16 BoTechology 2014 Ida Joural FULL PPER BTIJ, 10(16, 2014 [ ] Model for evaluatg the qualty for dstace educato based o the tellget computg wth tutostc fuzzy formato Xe Yog Moder Educato Techology Ceter, X'a Iteratoal Uversty, X'a , (CHIN BSTRCT I ths paper, we vestgate the multple attrbute decso makg problems for evaluatg the qualty of Dstace educato based o the tellget computg wth tutostc fuzzy formato. We utlze the tutostc fuzzy Este weghted average (IFEW operator to aggregate the tutostc fuzzy formato correspodg to each alteratve ad get the overall value of the alteratves, the rak the alteratves ad select the most desrable oe (s accordg to the score fucto ad accuracy fucto. Fally, a llustratve example for evaluatg the qualty of Dstace educato based o the tellget computg wth tutostc fuzzy formato s gve. KEYWORDS Multple attrbute decso-makg (MDM; Itutostc fuzzy umbers; Itutostc fuzzy este weghted average (IFEW operator; Dstace educato. Trade Scece Ic.

2 9254 Model for evaluatg the qualty for dstace educato based o the tellget computg BTIJ, 10( INTRODUCTION Wth the rapd developmet of global servce dustry, especally uder the hstorc backgroud of greatly promotg moder servce dustry Cha, dstace educato s payg more ad more atteto to servce gradually. Dstace educato possesses the feature of "dustralzato", ad t s accompaed wth offerg ad usg vsble product, such as textbook; but ts fudametal product s stll educato servce ad ts core value derves from a seres of actvtes amog the servat (cludg teacher ad maager ad customer (studet of e-learg school ad study ceter. Therefore, dstace educato belogs to servce dustry, complyg wth basc rule of servce dustry, ad servce s the dustry essece of dstace educato [1-5]. From the perspectve of servce, the thess syllogstcally apples some relevat theory of servce dustry to dstace educato feld, whch have bee test the case study ad acto study, ad costructs a theoretcal system framework of dstace educato servce prelmary wth servce vew of "quas-publc product" of dstace educato as recogto foudato ad wth system vew, qualty vew, effcecy vew of dstace educato as the core. Vew o the product of dstace educato servce. The product of dstace educato servce s "quas-publc product", whch has the characterstcs of both publc product ad prvate product. I addto to teachg servce, the product of dstace educato servce abudatly cotas the servce of maagemet, the servce of facltes, the servce of campus culture, ad the servce for specal studets, whch are provded for the purpose of mprovg the qualty of teachg servces. Each of above metoed servces composes of four parts: explct servces, mplct servces, facltatg goods ad evromet, whch costruct the servce package of dstace educato orgac tegrty. Vew o the system of dstace educato servce [6-9]. The system of dstace educato servce cludes four elemets: "staff", "customers", "servce teracto"," equpmet ad evromet", whch carres out dstace educato servce ad creates the servce package of dstace educato together. Servce staff ad customers are the provder ad cosumer of dstace educato servce respectvely, equpmet ad evromet s ecessary codto of the servce, ad servce teracto s the core of the system, Sometmes, equpmet teracts wth customers drectly ad form servce teracto. Vew o the qualty of dstace educato servce [10-12]. The qualty of dstace educato servce dcates the degrees how dstace educato orgazatos satsfy the eeds of ther customers, such as studets, famles, eterprses, socetes, etc [13]. I ths paper, we vestgate the multple attrbute decso makg problems for evaluatg the qualty of Dstace educato based o the tellget computg wth tutostc fuzzy formato. We utlze the tutostc fuzzy Este weghted average (IFEW operator to aggregate the tutostc fuzzy formato correspodg to each alteratve ad rak the alteratves ad select the most desrable oe (s accordg to the score fucto. The remader of ths paper s set out as follows. I the ext secto, we troduce some basc cocepts related to tutostc fuzzy sets. I Secto 3 we troduce the MDM problem deal wth evaluatg qualty for Dstace educato based o the tellget computg wth tutostc fuzzy formato. I Secto 4, a llustratve example s poted out. I Secto 5 we coclude the paper ad gve some remarks. PRELIMINRIES I the followg, we troduce some basc cocepts related to IFS. Defto 1. IFS X s gve by {, μ(, ν ( } = x x x x X (1 where μ : X [ 0,1] ad ν : X [ 0,1], wth the codto μ( x ν( x umbers μ ( x ad ( x to the set [14-15] , x X. The ν represet, respectvely, the membershp degree ad o- membershp degree of the elemet x Defto 2. Let a = ( μ, ν ca be represeted as follows [16] : % be a tutostc fuzzy umber, a score fucto S of a tutostc fuzzy value (% =, S( a 1,1 [ ] S a μ ν %. (2 Defto 3. Let a = ( μ, ν value ca be represeted as follows [17] : % be a tutostc fuzzy umber, a accuracy fucto H of a tutostc fuzzy (% = +, H( a [ 0,1] H a μ ν %. (3

3 BTIJ, 10( Xe Yog 9255 to evaluate the degree of accuracy of the tutostc fuzzy value a% = ( μ, ν, where H( a [ 0,1] the value of H ( a%, the more the degree of accuracy of the tutostc fuzzy value a%. Defto 4. Let a% 1= ( μ1, ν1 ad a% 2= ( μ2, ν2 be two tutostc fuzzy values, ( s( a% = μ ν be the scores of a% ad b %, respectvely, ad let H( a% = μ + ν ad H( a = μ + ν degrees of a% ad b %, respectvely, the f S( a < S( b% the, (1 f H( a = H( b% %, the a% s smaller tha b %, deoted by a< b % %, the a% ad b % represet the same formato, deoted by a b s smaller tha b %, deoted by a% < b % [18]. %. The larger % ad s a = μ ν % be the accuracy % ; f S( a = S( b% % = % ; (2 f H( a < H( b% %, %, a% I the followg, we shall troduce the Este operatos o tutostc fuzzy sets ad aalyze some desrable propertes of these operatos. a% = μ, ν = 1,2, L, be a collecto of tutostc fuzzy values, ad let IFEW: Q Defto 5. [19] Let ( ( Q, f ε = 1 ( ω a% ( a% a% L a% IFEW,,, = ω 1 2 ω ω ω ( 1+ μ ( 1 μ 2 ν = 1 = 1 = 1 =, ω ω ω ω ( 1 μ ( 1 μ ( 2 ν ν = 1 = 1 = 1 = 1 T where = (,, L, be the weght vector of a ( = 1, 2,, ω ω1 ω2 ω % L, ad ω > 0, IFEW s called the tutostc fuzzy Este weghted averagg (IFEW operator. = 1 (4 ω = 1, the MODEL FOR EVLUTING THE QULITY FOR DISTNCE EDUCTION BSED ON THE INTELLIGENT COMPUTING WITH INTUITIONISTIC FUZZY INFORMTION The essece of the dstace educato s that the teachers ad learers separate, the teachg qualty caused order to remedy teachers ad studets to separate dopes, have offered servce of stadg umerous study for learers, the dstace educato ca make learers be able to study wheever ad wherever possble, but through lterature research of moder dstace educato learers ad documet of dstace educato, ad fd that t s more mportat to utlze ew techology ad etwork advatage establsh teachg model suted to dstace adult learers ad guarateeg teachg qualty. We frst lmted the dstace educato, bleded learg ad teachg model respectvely through the theory research, the we desged the teachg model of dstace educato based the theory of dstace educato, bleded learg ad trasmsso though may research method, at last we brought forward a ew teachg model--bleded learg model dstace educato. I ths paper, we vestgate the multple attrbute decso makg problems for evaluatg the qualty of Dstace educato based o the tellget computg wth tutostc fuzzy formato. Let T { S1, S2,, Sm} dscrete set of schools. Let G { G1, G2,, G} completely kow. Let ω = ( ω ω L ω be the weght vector of attrbutes, whereω 0, 1, 2,, that R= ( r = ( μν, m m = L be a = L be a set of attrbutes. The formato about attrbute weghts s 1, 2,, = L. Suppose % % s the tutostc fuzzy decso matrx, where μ dcates the degree that the alteratve satsfes the attrbute G gve by the decso maker, ν dcates the degree that the alteratve does t satsfy the attrbute G gve by the decso maker D k, μ [ 0,1], ν [ 0,1], μ + ν 1, = 1, 2, L, m, = 1, 2, L,, k = 1, 2, L, t.

4 9256 Model for evaluatg the qualty for dstace educato based o the tellget computg BTIJ, 10( I the followg, we apply the IFEW operator to evaluate the qualty for Dstace educato wth tutostc fuzzy formato. Step 1. Utlze the decso formato gve matrx R %, ad the IFEW operator ( μν ( r% =, =IFEW r%, r%, L, r%, = 1, 2, L, m. (5 ω 1 2 to derve the values r% ( = 1, 2, L, m of the alteratve S. Step 2. Calculate the scores Sr ( % ( = 1, 2, L, m of the tutostc fuzzy preferece values r% ( = 1, 2, L, m to rak all the alteratves S ( = 1, 2, L, m ad the to select the best oe (s. Step 3. Rak all the schools S ( = 1, 2, L, m ad select the best oe (s accordace wth S( r% ad H ( r% ( = 1, 2, L, m. NUMERICL EXMPLE Sce the mddle of 19th cetury, the mode of dstace educato has greatly chaged wth the developmet of commucato techology. t preset, based o the developmet ad applcato of formato techology, dstace educato experts dvde the developg process of dstace educato to three phases: correspodece educato from the mddle of 19th cetury to the mddle of 20th cetury, multmeda-aded dstace educato from the mddle of 20th cetury to the ed of 1980s ad Web-based dstace learg sce 1990s. The chage of teachg mode always brgs a seres of problems whch we ca ot avod. I the late of 1990s, two-way vdeo coferecg system based o satellte ad Iteret techology were employed by Rado ad Televso Uverstes at all levels across Cha. Sce 1998, more ad more uverstes have started to offer dstace educato courses. d by the ed of 2003, the umber of uverstes whch mplemet tral Web-based structo has amouted to 68, cludg the Cetral Rado ad Televso Uversty. However, the rapd expaso of scale ad the lack of expereces have resulted varous problems, the reducto of teachg qualty ad socal trust. The ma problems are as follows: o complete qualty guaratee system, o ufed qualty stadards, o forceful supervso of the teachg process, low effcecy of et learg, the lack of systematc teachg support ad servce, the lack of practcal techque trag for farmers ad the combato of school ad eterprse. Faced wth the curret stuato of moder dstace educato, educators should aalyze these problems carefully, fd out the causes ad come up wth reasoable suggestos so as to keep dstace educato growg steadly. The followg thess s a attempt to explore seres of exstg problems based o the research whch has bee doe both at home ad abroad wth regard to the mode of dstace educato ad the wrter wll, terms of the socal demad ad the practcal problems of web based structo, rase some measures to be take ad suggestos to further perfect dstace educato. Ths secto presets a umercal example to llustrate the method proposed ths paper. There s a pael wth fve possble Dstace educato = to select. The experts select four attrbute to evaluate the fve Dstace educato schools: 1G 1 schools ( 1, 2,3, 4, 5 s the evromet of teachg ad studyg; 2G 2 s the maagemet of teachg formato; 3G 3 s the currculum desg ad target; 4G 4 s the empathy ad the teachg practce. The fve possble Dstace educato schools ( = 1, 2,3, 4, 5 are to be evaluated usg the tutostc fuzzy formato by the decso maker uder the above four attrbutes whose 0.30,0.10,0.40,0.20 T, as lsted the followg matrx. weghtg vector ω = ( %= G1 G2 G3 G4 ( 0.4,0.6 ( 0.3,0.5 ( 0.7,0.3 ( 0.3,0.4 ( 0.5, 0.4 ( 0.6, 0.2 ( 0.2, 0.2 ( 0.6, 0.2 ( 0.5, 0.3 ( 0.5, 0.2 ( 0.6, 0.4 ( 0.6, 0.1 ( 0.2, 0.3 ( 0.8, 0.2 ( 0.5, 0.2 ( 0.5, 0.4 ( 0.6, 0.46 ( 0.6, 0.1 ( 0.4, 0.4 ( 0.7, 0.2 The, we utlze the approach developed to evaluate qualty of Dstace educato order to select the best Dstace educato schools.

5 BTIJ, 10( Xe Yog 9257 Step 1. Utlze the IFEW operator, we obta the preferece values r% of the Dstace educato schools ( 1, 2,3, 4, 5 =. ( 0.47,0.22, ( 0.65, 0.31, ( 0.54, 0.21 ( 0.59, 0.14, r ( 0.76, 0.12 r% 1 = r% 2 = r% 3 = r% = % = 4 5 Step 2. Calculate the scores S( r% ( = 1, 2,3, 4,5 of the tutostc fuzzy values r% ( = 1, 2,3, 4,5 (% (% (% (% = 0.45, S( r% = 0.64 S r = 0.25, S r = 0.34, S r = 0.33 S r 4 5 Step 3. Rak all the Dstace educato schools ( = 1, 2,3, 4, 5 accordace wth the scores S( r% ( = 1, 2,3, 4,5 of the overall tutostc fuzzy values r ( = 1, 2, 3, 4, 5 most desrable Dstace educato school s 5. % : CONCLUSION f f f f, ad thus the I ths paper, we vestgate the multple attrbute decso makg problems for evaluatg the qualty of Dstace educato based o the tellget computg wth tutostc fuzzy formato. We utlze the tutostc fuzzy Este weghted average (IFEW operator to aggregate the tutostc fuzzy formato correspodg to each alteratve ad get the overall value of the alteratves, the rak the alteratves ad select the most desrable oe (s accordg to the score fucto ad accuracy fucto. Fally, a llustratve example for evaluatg the qualty of Dstace educato based o the tellget computg wth tutostc fuzzy formato s gve. CKNOWLEDGMENT Ths paper s supported by the Shaax Educato Scece "secod fve" plag ssues SGH REFERENCES [1] Pede Lu, Y.Su; The exteded TOPSIS based o trapezod fuzzy lgustc varables, Joural of Covergece Iformato Techology, 5(4, (2010. [2] Hog Ta, Guwu We; "OWCLCO Operator ad ts pplcato to Comprehesve Evaluatg Modelg of Brad Exteso Ucerta Lgustc Settg", JCIT: Joural of Covergece Iformato Techology, 6(7, (2011. [3] Jal We; "TOPSIS Method for Multple ttrbute Decso Makg wth Icomplete Weght Iformato Lgustc Settg", JCIT: Joural of Covergece Iformato Techology, 5(10, (2010. [4] Mghe Wag, Pede Lu; " Exteded VIKOR Method for Ivestmet Rsk ssessmet of Real Estate based o the Ucerta Lgustc Varables", ISS: dvaces Iformato Sceces ad Servce Sceces, 3(7, (2011. [5] Xaorog Wag, Zhahog Gao, Guwu We; " pproach to rchves Webstes Performace Evaluato Our Coutry wth Iterval Itutostc Fuzzy Iformato", ISS: dvaces Iformato Sceces ad Servce Sceces, 3(7, (2011. [6] Juch Hou; "Grey Relatoal alyss Method for Multple ttrbute Decso Makg Itutostc Fuzzy Settg", Joural of Covergece Iformato Techology, 5(10, (2010. [7] W.L.Hug, M.S.Yag; Smlarty measures of tutostc fuzzy sets based o L-p metrc, Iteratoal Joural of pproxmate Reasog, 46(1, Sep (2007. [8] W.L.Hug, M.S.Yag; O the J-dvergece of tutostc fuzzy sets wth ts applcato to patter recogto, Iformato Sceces, 178(6, Mar (2008. [9] D.K.Iakovds, E.Papageorgou; Itutostc Fuzzy Cogtve Maps for Medcal Decso Makg, Ieee Trasactos o Iformato Techology Bomedce, 15(1, Ja (2011. [10] Y.C.Jag, Y.Tag, Q.M.Che; adustable approach to tutostc fuzzy soft sets based decso makg, ppled Mathematcal Modellg, 35(2, Feb (2011. [11] Y.C.Jag, Y.Tag, Q.M.Che; adustable approach to tutostc fuzzy soft sets based decso makg ppled Mathematcal Modellg, 35(5, May (2011.

6 9258 Model for evaluatg the qualty for dstace educato based o the tellget computg BTIJ, 10( [12] Y.C.Jag, Y.Tag, Q.M.Che et al.; Iterval-valued tutostc fuzzy soft sets ad ther propertes, Computers & Mathematcs wth pplcatos, 60(3, ug (2010. [13].Kharal; Homeopathc drug selecto usg Itutostc Fuzzy Sets, Homeopathy, 98(1, Ja (2009. [14] K.taassov; Itutostc fuzzy sets, Fuzzy Sets ad Systems, 20(3, (1986. [15] K.taassov; More o tutostc fuzzy sets, Fuzzy Sets ad Systems, 33(5, (1989. [16] S.M.Che, J.M.Ta; Hadlg multcrtera fuzzy decso-makg problems based o vague set theory, Fuzzy Sets ad Systems, 67(4, (1994. [17] D.H.Hog, C.H.Cho; Multcrtera fuzzy problems based o vague set theory, Fuzzy Sets ad Systems, 114(3, (2000. [18] Zeshu Xu; Itutostc fuzzy aggregato operators, IEEE Trasatos o Fuzzy Systems, 15(6, (2007. [19] Weze Wag, Xwag Lu; Itutostc Fuzzy Iformato ggregato Usg Este Operatos, IEEE Trasactos o Fuzzy Systems, 20(2, (2012.