The use of linear parametric approximation in numerical solving of nonlinear non-smooth Fuzzy equations

Similar documents
Certain Expansion Formulae Involving a Basic Analogue of Fox s H-Function

Numerical Methods for Eng [ENGR 391] [Lyes KADEM 2007] Direct Method; Newton s Divided Difference; Lagrangian Interpolation; Spline Interpolation.

ECONOMETRIC ANALYSIS ON EFFICIENCY OF ESTIMATOR ABSTRACT

Difference Sets of Null Density Subsets of

Fredholm Type Integral Equations with Aleph-Function. and General Polynomials

2. Elementary Linear Algebra Problems

Chapter #2 EEE State Space Analysis and Controller Design

SOME REMARKS ON HORIZONTAL, SLANT, PARABOLIC AND POLYNOMIAL ASYMPTOTE

2.Decision Theory of Dependence

Numerical Solution of Fractional Telegraph Equation Using the Second Kind Chebyshev Wavelets Method

-HYBRID LAPLACE TRANSFORM AND APPLICATIONS TO MULTIDIMENSIONAL HYBRID SYSTEMS. PART II: DETERMINING THE ORIGINAL

On Almost Increasing Sequences For Generalized Absolute Summability

The shifted Jacobi polynomial integral operational matrix for solving Riccati differential equation of fractional order

Chapter 17. Least Square Regression

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

ANOTHER INTEGER NUMBER ALGORITHM TO SOLVE LINEAR EQUATIONS (USING CONGRUENCY)

Chapter Linear Regression

PENALTY FUNCTIONS FOR THE MULTIOBJECTIVE OPTIMIZATION PROBLEM

University of Pavia, Pavia, Italy. North Andover MA 01845, USA

Describes techniques to fit curves (curve fitting) to discrete data to obtain intermediate estimates.

A Unified Formula for The nth Derivative and The nth Anti-Derivative of the Bessel Function of Real Orders

E-Companion: Mathematical Proofs

SYSTEMS OF NON-LINEAR EQUATIONS. Introduction Graphical Methods Close Methods Open Methods Polynomial Roots System of Multivariable Equations

X-Ray Notes, Part III

Regularization of the Divergent Integrals I. General Consideration

φ (x,y,z) in the direction of a is given by

= y and Normed Linear Spaces

A Credibility Approach for Fuzzy Stochastic Data Envelopment Analysis (FSDEA)

Multiple Attribute Group Decision Making using Interval-Valued Intuitionistic Fuzzy Soft Matrix

Efficient Estimator for Population Variance Using Auxiliary Variable

Asymptotic Dominance Problems. is not constant but for n 0, f ( n) 11. 0, so that for n N f

SOLVING SYSTEMS OF EQUATIONS, DIRECT METHODS

3. REVIEW OF PROPERTIES OF EIGENVALUES AND EIGENVECTORS

PARAMETRIC STUDY ON PARETO, NASH MIN- MAX DIFFERENTIAL GAME

ICS141: Discrete Mathematics for Computer Science I

African Journal of Science and Technology (AJST) Science and Engineering Series Vol. 4, No. 2, pp GENERALISED DELETION DESIGNS

Chapter 2: Descriptive Statistics

SEPTIC B-SPLINE COLLOCATION METHOD FOR SIXTH ORDER BOUNDARY VALUE PROBLEMS

Maximum likelihood estimate of phylogeny. BIOL 495S/ CS 490B/ MATH 490B/ STAT 490B Introduction to Bioinformatics April 24, 2002

The formulae in this booklet have been arranged according to the unit in which they are first

Spectral Continuity: (p, r) - Α P And (p, k) - Q

On The Circulant K Fibonacci Matrices

Super-Mixed Multiple Attribute Group Decision Making Method Based on Hybrid Fuzzy Grey Relation Approach Degree *

In Calculus I you learned an approximation method using a Riemann sum. Recall that the Riemann sum is

NONDIFFERENTIABLE MATHEMATICAL PROGRAMS. OPTIMALITY AND HIGHER-ORDER DUALITY RESULTS

A convex hull characterization

Journal of Engineering and Natural Sciences Mühendislik ve Fen Bilimleri Dergisi SOME PROPERTIES CONCERNING THE HYPERSURFACES OF A WEYL SPACE

L. Yaroslavsky. Selected Topics in Image Processing Part 1. Imaging transforms in digital computers

Occurrences of ordered patterns in rectangular space filling curve through homomorphism

A Dynamical Quasi-Boolean System

Differential Entropy 吳家麟教授

International Mathematical Forum, Vol. 9, 2014, no. 13, HIKARI Ltd,

MTH 146 Class 7 Notes

6.6 Moments and Centers of Mass

On Optimal Termination Rule for Primal-Dual Algorithm for Semi- Definite Programming

The formulae in this booklet have been arranged according to the unit in which they are first

FRACTIONAL MELLIN INTEGRAL TRANSFORM IN (0, 1/a)

ME 501A Seminar in Engineering Analysis Page 1

Elastic-Plastic Transition of Transversely. Isotropic Thin Rotating Disc

are positive, and the pair A, B is controllable. The uncertainty in is introduced to model control failures.

Integral Solutions of Non-Homogeneous Biquadratic Equation With Four Unknowns

CURVE FITTING LEAST SQUARES METHOD

GCE AS and A Level MATHEMATICS FORMULA BOOKLET. From September Issued WJEC CBAC Ltd.

14. MRAC for MIMO Systems with Unstructured Uncertainties We consider affine-in-control MIMO systems in the form, x Ax B u f x t

Nonlocal Boundary Value Problem for Nonlinear Impulsive q k Symmetric Integrodifference Equation

Complex Variables. Chapter 19 Series and Residues. March 26, 2013 Lecturer: Shih-Yuan Chen

THE PUBLISHING HOUSE PROCEEDINGS OF THE ROMANIAN ACADEMY, Series A, OF THE ROMANIAN ACADEMY Volume 6, Number 1/2005, pp

Analysis of Electromagnetic Wave Scattering from a Fourier Grating Multilayer-Coated Metallic Grating in Conical Mounting

. The set of these sums. be a partition of [ ab, ]. Consider the sum f( x) f( x 1)

An Alternative Method to Find the Solution of Zero One Integer Linear Fractional Programming Problem with the Help of -Matrix

IO Gender and natural history

RECAPITULATION & CONDITIONAL PROBABILITY. Number of favourable events n E Total number of elementary events n S

ON THE STRUCTURE OF THE EULER MAPPING

The linear system. The problem: solve

Some Equivalent Forms of Bernoulli s Inequality: A Survey *

Three Phase Asymmetrical Load Flow for Four-Wire Distribution Networks

rad / sec min rev 60sec. 2* rad / sec s

Calculus 241, section 12.2 Limits/Continuity & 12.3 Derivatives/Integrals notes by Tim Pilachowski r r r =, with a domain of real ( )

A Study on New Sequence of Functions Involving the Generalized Contour Integral

Observations on the transcendental Equation

Mean Cordial Labeling of Certain Graphs

Basic Structures: Sets, Functions, Sequences, and Sums

Some Integrals Pertaining Biorthogonal Polynomials and Certain Product of Special Functions

COMP 465: Data Mining More on PageRank

χ be any function of X and Y then

SUBSEQUENCE CHARACTERIZAT ION OF UNIFORM STATISTICAL CONVERGENCE OF DOUBLE SEQUENCE

Moments of Generalized Order Statistics from a General Class of Distributions

LECTURE 8: Topics in Chaos Ricker Equation. Period doubling bifurcation. Period doubling cascade. A Quadratic Equation Ricker Equation 1.0. x x 4 0.

International Journal of Scientific and Research Publications, Volume 3, Issue 5, May ISSN

Maximize: x (1.1) Where s is slack variable vector of size m 1. This is a maximization problem. Or (1.2)

On the Trivariate Polynomial Interpolation

Name: Period: Date: 2.1 Rules of Exponents

Mathematical Statistics

BEM with Linear Boundary Elements for Solving the Problem of the 3D Compressible Fluid Flow around Obstacles

Analysis of error propagation in profile measurement by using stitching

On Several Inequalities Deduced Using a Power Series Approach

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

5 - Determinants. r r. r r. r r. r s r = + det det det

Available online through

148 CIVIL ENGINEERING

Transcription:

vlle ole t www.choleechl.co chve o ppled Scece Reech 5 6:49-6 http://choleechl.co/chve.htl ISSN 975-58X CODEN US SRC9 The ue o le petc ppoto uecl olvg o ole o-ooth uzz equto Mjd Hllj e Ze d l Vhd Kd Nehu Bch Ilc zd Uvet Nehu I od Bch Ilc zd Uvet od I edow Uvet Mhd I BSTRCT I th ppoch The le petc ppoto the ole ucto ppoted pecewe le ucto. The oted oluto h dele ccuc d the eo copletel cotollle. Wth eteo th ppoch we popoe ew two-tep tetve ethod o olvg ole uzz equto d ole o-ooth uzz equto. ll oe uecl eple e gve to how the ecec o the popoed ppoch to olve e equto the othe eeece. Ke wod: Tlo le epo Le Petc ppoto ole o-ooth uzz ucto. INTRODUCTION I ecet e uch tteto h ee gve to develop tetve tpe ethod o olvg ole equto lke. Becue the Ste o ulteou ole equto pl jo ole vou e uch thetc tttc egeeg d ocl cece. The cocept o uzz ue d thetc opeto wth thee ue wee t toduced d vetgted 58 57. Oe o the jo pplcto o uzz ue thetc ole equto whoe pete e ll o ptll epeeted uzz ue 6. Stdd ltcl techque peeted Buckle d Qu 5. Stdd ltcl techque lke Buckle d Qu ethod 4 cot e utle o olvg the equto uch : 5 g 4 c d e Whee c d e d g e uzz ue. Moeove ou o clcl uecl ethod uch : Newto d Newto-Rpho e ule to olve the o-ooth equto uch : equto.we theeoe eed to develop the uecl ethod to d the oot o uch equto. Hee we code thee equto geel :. 49

Mjd Hllj et l ch. ppl. Sc. Re. 5 6:49-6 I th ppe we toduce ew ppoch to olve ppotel ole o-ooth uzz equto whch do t hve ltto upo covet d oothe o the ole uzz ucto. I th ppoch gve ole uzz ucto ppoted pecewe le ucto wth cotolled eo whch ed o geelzto o Tlo le epo o ooth ucto. lo we epeet ecet lgoth to olve o ppoted uzz pole. Oe o the dvtge o ou ppoch tht t c e eteded to pole wth ole o-ooth uzz ucto toducg ovel deto o lol Wek Deetto the ee o L-o 9. The ppe ogzed ollow: I Secto two we ecll oe udetl eult o uzz ue. I ecto thee we epl the ppoch o le petc ppoto o ole equto. We ve the outh ecto the ppoch eteded o o-ooth ole equto toducg the deto o glol wek deetto. We eteded the ppoch ecto ve o olvg uzz ole equto. I the th ecto the ppoch w eteded o olvg o o-ooth ole uzz equto. ll oe lluttve eple d cocluo e gve to how the eectvee o the popoed ppoch.. Pele Deto.. uzz ue uzz et lke u : R I whch te 968. u uppe e cotuou. u outde oe tevl c d. Thee e el ue uch tht c d d. u ootoc ceg o c. u ootoc deceg o d. u. The et o ll thee uzz ue deoted E. equvlet petc lo gve ollow. Deto.. uzz ue u petc o p u u u u whch te the ollowg equeet:. u ouded ootoc ceg let cotuou ucto. u ouded ootoc deceg let cotuou ucto. u u. o ucto popul uzz ue the tpezodl uzz ue σ β let uzze σ d ght uzze β whee the eehp ucto : u wth tevl deuzze d σ σ u β β It petc o : σ othewe. β u σ σ u β β. Let T R e the et o ll tpezodl uzz ue. The ddto d cl ultplcto o uzz ue e deed the eteo pcple d c e equvletl epeeted ollow. o t u u u v v v d k > we dee ddto u v d ultplcto cle k : 5

Mjd Hllj et l ch. ppl. Sc. Re. 5 6:49-6 u v u v ku ku u v u v ku ku.. The ppoch o le petc ppoto o ole equto 9 Code the ole ooth ucto. We ppote the ole ucto pecewe le ucto deed o. Let u eto the ollowg deto. Deto.. Let P e ptto o the tevl the o: P {... } Whee h d h. The o o ptto deed : P { } It e to how tht P. Deto.. The ucto deed ollow: ; K whee t pot. The ucto clled the le petc ppoto o o t the pot. I uul le epo the pot ed ut hee we ue ee pot. Now we dee g the petc le ppoto o o octed wth the ptto P ollow: g χ whee χ the chctetc ucto d deed elow: χ. The ollowg theoe e how tht g covegece uol to the ogl ole ucto whe. I the othe wod we how tht: P g uol o P The ollowg theoe e how tht g covegece uol to the ogl ole ucto whe P. the othe wod we how tht: g uol o P 5

Mjd Hllj et l ch. ppl. Sc. Re. 5 6:49-6 Le.. Let P e t egul ptto o. I cotuou ucto o d e t pot the: l. P Poo. The poo edte coequece o the deto. Th le how tht g pot-we o. Deto.. l o cople ucto deed o et etc pce X d to e equcotuou o o eve ε > thee et δ > uch tht wheeve d < δ. Hee d deote the etc o ee 7. Sce { g } equece < ε o le ucto t tvl tht th equece equcotuou. Theoe.. Let { } equcotuou equece o ucto o copct et d { } covege potwe o. The { } covege uol o. Poo. See 9. Theoe.. Let g pecewe le ppoto o o g uol o.. The: Poo. The poo edte coequece o Le. d Theoe. 9. Now we toduce ovel deto o glol eo o ppoted wth le petc ucto g the ee o L-o whch utle cteo to how the goode o ttg. Deto.4. Let e ole ooth ucto deed o d let g deed 4 e petc le ppoto o.let the glol eo o ppoto o the ucto wth ucto g the ee o L -o deed ollow: E g d d It e to how tht E ted to zeo uol whe. Th deto ued to ke the e ptto whch tched wth dele ccuc. 4. Eteo o le petc ppoto o olvg uzz ole equto Now ou to ot oluto o uzz ole equto. The petc o o two tep ethod ollow: P 5

Mjd Hllj et l ch. ppl. Sc. Re. 5 6:49-6 5 Theeoe ue the le petc ppoto ppoch geelzto o Tlo le epo o ooth ucto o the we dee the ucto ollow: ; ; K whee d e t pot. The ucto clled the lowe oud le petc ppoto o o t the pot d clled the uppe oud le petc ppoto o o t the pot. Now we dee the petc le ppoto o o octed wth the ptto P ollow: χ χ 4 whee d χ χ e the lowe oud d uppe oud chctetc ucto epectvel d deed elow: χ χ 5 The ollowg theoe e how tht covegece uol to the ogl ole uzz equto whe P. I the othe wod we how tht: Le 4.. Let P e t egul ptto o. I d e cotuou ucto o d e t pot the:. l P 6 Poo. The poo edte coequece o the deto. Th le how tht pot-we o. o uol P

Mjd Hllj et l ch. ppl. Sc. Re. 5 6:49-6 54 Be o deto.4 d eteo o t d e equece o le uzz ucto t tvl tht th equece equcotuou. Moeove e o Theoe. d covege uol o etc pce X X epectvel. Theoe 4.. Let { }d { } e equcotuou equece o ucto o copct et o epectvel d { } { } covege pot-we o. The { } { } covege uol o epectvel. Poo. Sce { } { } e equece o equcotuou uzz ucto o the:. ; ; L < < < < > > d d.t ε ε δ δ δ ε o ech thee et > δ uch tht U N δ U N δ.sce e copct th ope coveg o hve te u-coveg. Thu thee et te ue o pot uch : K d K uch tht U N δ U N δ.theeoe o ech d thee et epectvel o ; K uch tht: < < δ δ d d We kow e pot-we coveget equece the thee et tul ue N uch tht o ech N N we hve:. ε 7. ε 8 The ccodg to the Theoe 7.8 7 the equece } }{ { e uol cotuou o d the poo copleted. Theoe 4.. Let d e pecewe le ppoto o epectvel o. 4. The: o uol. Poo. The poo edte coequece o Le. d Theoe..

Mjd Hllj et l ch. ppl. Sc. Re. 5 6:49-6 5.Eteo to ole o-le o-ooth uzz equto I geel t eole to ue tht the ojectve ucto o-oothe. Theeoe we dee kd o geelzed deetto o o-ooth ucto the ee o L-o. Th kd o deetto cocdg wth uul deetto o ooth ucto. Theeoe the ollowg theoe epeeted. Theoe 5.. Code the ole o-ooth ucto : R whee. The the optl oluto o the ollowg optzto pole. Mze P. K. p d Kd 9 whee K t pot d P. P. P. K P. vecto. Poo. See. Deto 5.. Let : R o-ooth ucto whee. The glol wek deetto wth epect to the ee o L-o deed the P. the optl oluto o the zto pole whch how 9. Now ed o Theoe 4. d deto 4.we popoed eteo ethod o o-le o-ooth uzz ucto ollowg: Code the ole o-ooth uzz ucto. Bed o Theoe 4.we hve o-ooth uzz pole ollow: Mze P.. p dd K Whee : p p d. p Wth ue o two tep ethod o-ooth uzz pole covet ollow: Mze K P.. p d d Mze K. p dd P. d ed we ue o VK ethod o olvg ove pole.wth uppoe.5 uzz zto pole 9 oed : Mze p.. p dd Rek: we kow ppote vlue o tegl c. o-ooth kd k c whee c pot uch : 55

Mjd Hllj et l ch. ppl. Sc. Re. 5 6:49-6 So ed two tep ethod VK ethod pplg ove ek d ue c edg pot utevl d ddle pot o oed : Mze p. Mze p. Whee :. p. p d. whole pole NLP pole d we ot t oluto pckge uch LgoMtl o etc. 6. Nuecl pplcto Hee we peet eple to lluttg the le petc ppoto ethod o d potve oot o ole uzz equto d ole o-ooth uzz equto. Eple d code o Buckle Qu d S. d B. d. Eple 6.. Code the uzz ole equto 45 Wthout lo o geelt ue tht potve d the the petc o o th equto ollow: 5 To ot tl gue we ue ove te o theeoe: 4 d ; 4 5 we ot the oluto o d wth the Me qued olzed eo MSE7.9e-7. o oe detl ee g.. Now uppoe egtve hece > theeoe egtve oot doe ot et. Eple 6.. Code uzz ole equto 4 45 58 Wthout lo o geelt ue tht potve d the petc o o th equto ollow: 5 5 5 O eqult: 8 4 We ppl popoed ethod o d how eult g. wth MSE 9.677e-7. 56

Mjd Hllj et l ch. ppl. Sc. Re. 5 6:49-6 Eple 6.. I th eple we code ole o-ooth uzz ucto ollow: 45 Sce ojectve ucto o-ooth uzz ucto. We d the glol wek deetto o whch the optl oluto o the ollowg optzto pole.we olve th pole ed two tep ethod d VK ethod o d wth uppoe Mze p. Mze p. p. p. Mze Mze ollow: p d 5 5 p d p 5 5 p Lt equto NLP pole d we ot t oluto Mtl otwe.the optl oluto how g.. ll we d uzz potve oot o ed popoed ethod pecewe le ppoto g.4. Tle 5. cope ppoted d ect oluto o lt eple. Copo eult how the eectvee o the popoed ppoch the peece o uzz ole o-ooth ucto Tle 5.-Nuecl Reult o Eple o Nole Noooth uzz ucto 4 l cut Me qued olzed eo Ect oluto Lowe Boud ppoted oluto Ect oluto Uppe Boud ppoted oluto..4458545985.456454794.566865967.56946754..444457456.444757755874.58455649.588788758..45944875685.45855455.558969647.558885588..46857748.4654674675.57974946.5477797856.4.46858749855.46875757.55687475.59458744.5.474546489995.475799669.5765675756.5879597.6.4856467884.4895985494.54568548974.5574987.7.48597669979.487549558.587795.5489794.8.49666768945.498879946.577785.595674.9.49567789456.4978465878.545646978.557445669..5987.544877996.5987.544877996.774598876e-6 57

Mjd Hllj et l ch. ppl. Sc. Re. 5 6:49-6.9.8 Etted Potve Root Rel Potve Root.7 L CUTS.6.5.4....4.44.46.48.5.5.54.56 Potve Root g.. Potve oluto o popoed ethod.9 Etted Ptve Root Rel Potve Root.8.7 L CUTS.6.5.4....8.85.9.95.5..5 Potve Root g.. Potve oluto d eo o popoed ethod 58

Mjd Hllj et l ch. ppl. Sc. Re. 5 6:49-6 5 Blck : Wek Deeto o Blue : Wek Deeto o << Red : Wek Deeto o lol Wek Deeto 5-5 - -5 - -.8 -.6 -.4 -...4.6.8 g-lol Wek Deetto o Nole No-Sooth ucto 45.9.8 Etted Root Rel Root.7.6 l cut.5.4....4.44.46.48.5.5.54.56 g 4. Potve oot o o-ooth uzz ucto Bed Pecewe le ppoto CONCLUSION I th ppe we hve uggeted uecl olvg ethod o o-le uzz equto ted o tdd ltcl techque whch e ot utle evewhee. lo the ppoch c e eteded o o-le o- 59

Mjd Hllj et l ch. ppl. Sc. Re. 5 6:49-6 ooth uzz equto ovel deto o glol wek deetto the ee o L d LP o. The dvtge o th ppoch tht we oted ppoto o the optu oluto o the uzz pole wth dele ccuc. Itll we wote ole d o-ooth uzz equto petc o d the olve t the le petc ppoto ethod. ll eple wee peeted to llutte popoed ethod. REERENCES J.J. Buckle Y. Qu uzz Set d Ste 8 99 4 59. J.J. Buckle Y. Qu uzz Set d Ste 8 99 9. J.J. Buckle Y. Qu uzz Set d Ste 9 99 9. 4 J.J. Buckle Y. Qu uzz Set d Ste 4 99 4. 5 S.S.L. Chg L.. Zdeh O uzz ppg d cotol IEEE Tcto o Ste M d Ceetc 97 4. 6 Y.J. Cho N.J. Hug S.M. Kg uzz Set d Ste 5. 7 J.E. De R.B. Schel Nuecl Method o Ucoted Optzto d Nole Equto Petce-Hll New Jee 98. 8 D. Duo H. Pde Joul o Ste Scece 9 978 6 66. 9 D. Duo H. Pde uzz Set d Ste: Theo d pplcto cdec Pe New Yok 98. J. g uzz Set d Ste 57 64. R. oetchel W. Vo uzz Set d Ste 8 986 4. J. M. eg uzz Set d Ste.7 67 86. M. Mzuoto Soe popete o uzz ue : M.M. upt R.K. Rgde R.R. Yge Ed. dvce uzz Set Theo d pplcto Noth-Holld ted 979 pp. 56 64. 4 M. Mzuoto K. Tk Ste Copute d Cotol 7 5 976 7 8. 5 S. Nh uzz Set d Ste 978 97. 6 L.. Zdeh uzz et Ioto d Cotol 8 965 8 5. 7 L.. Zdeh Ioto Scece 975 99 49. 8 H.J. Ze uzz Set Theo d t pplcto Kluwe cdec Pe Dodecht 99. 9.M. Vz.V. Kd. Jj S. Et Coputtol d ppled Mthetc Volue N. pp. 47 44. S. d B. d ppled Mthetc d Coputto 59 4 49 5. K.P. Bdkhh.V. Kd. ze ppled Mthetc d Coputto 89 7 7 4..M. Vz.V. Kd S. Et d M. chpz petc lezto ppoch o olvg ole pogg pole lgh Joul Stttc tcle pe. 6