EVALUATION MODEL OF FUZZY DATA AND NEURAL NETWORK IN MARTIAL ART COMPETITION

Transcription

1 Jounal of heoetical and Applied Infoation echnology 8 th Febuay 3 Vol 48 No3 5-3 JAI & LLS All ights eseved ISSN: wwwatitog E-ISSN: EVALUAION MODEL OF FUZZY DAA AND NEURAL NEWORK IN MARIAL AR COMPEIION HAI YU Shenyang Spots Univesity Shenyang Liaoning China E-ail: wushuxy@6co ABSRAC Due to the abiguity of the esults given by the efeee in Matial at copetition the design of a set of fai and ipatial scientific and ational evaluation syste is paticulaly ipotant his pape builds a fuzzy copehensive evaluation odel based on the fuzzy nube theoy As this odel has a high degee of subectivity this aticle cobines RBF neual netwok odel and data envelopent analysis ethod with fuzzy copehensive evaluation odel and establishes two kinds of evaluation odel as fuzzy data envelopent analysis and fuzzy neual netwok solving the eliability and scientific issue of the evaluation esult appopiately Keywods: Matial At Fuzzy Data Neual Netwok INRODUCION Matial at in aboad is ainly focused on the quantization and digitization of the athletes taining who have good physical ability In this way the oveloading physical taining can enhance the athletes ability in a shot peiod of tie and ay possibly cultivate an outstanding athlete in two o thee yeas Howeve this quick success of taining often esults in the ealy ending of the athlete s pofessional caee Quantization and digitization possess cetain advantages but it is not pefect and appopiate fo diffeent people and cultue Chinese Matial at should aintain its own unique advantages in the developing pocess as well as absobing scientific anageent ode and advanced taining ethods fo the west [-3] In Matial at copetitions efineent of aking citeion shote copetition tie and diffeence of efeee ability et al all affect atial ats athletes pactice level and copletion esult [4-6] heefoe it is paticulaly ipotant to design a set of a set of fai and ipatial scientific and ational evaluation syste All these factos have cetain degee of fuzziness such as the scoes ae usually subectively deteined given by the efeee and atificially subective effects ae also eflected in the foulation of evaluation standad [7-9] his aticle builds a fuzzy copehensive evaluation odel on the basis of fuzzy nube theoy Due to the high subectivity of this odel this eseach cobines RBF neual netwok odel and data envelopent analysis ethod with fuzzy copehensive evaluation odel enhancing the eliability and scientificalness of this evaluation odel EVALUAION MODEL OF FUZZY DAA ENVELOPMEN ANALYSIS Data envelopent analysis is a odel based on atheatical pogaing (including linea pogaing ultiple obective pogaing and et al and evaluates the elative effectiveness between decision aking units with ulti-inputs and especially ulti-outputs he advantage of this odel is the accuacy of the obective data but it is often difficult to find accuate data of indicatos and factos in pactical life as a esult this odel is of cetain fuzziness [ 3 7] his aticle copleents the fuzziness of fuzzy copehensive evaluation with the accuacy of data envelopent analysis and builds a fuzzy copehensive evaluation odel of data envelopent analysis hee ae ainly thee steps in this pocess: the fist step is the bluing opeation of the nonquantitative indexes weights; the second step is efined calculation of the quantitative indexes weights using data envelopent analysis and fuzzification of the opeation esult; the thid step is fuzzy copehensive evaluation of the above esults and eaching a final evaluation conclusion Suppose that the nube of evaluation units evaluation indexes quantitative indexes and nonquantitative indexes is and espectively 458

2 Jounal of heoetical and Applied Infoation echnology 8 th Febuay 3 Vol 48 No3 5-3 JAI & LLS All ights eseved ISSN: wwwatitog E-ISSN: Bluing Opeation of Non-Quantitative Weights C = ( c c cq If is the facto set and V = ( v v v p is the coent set then the copehensive evaluation atix is: R = q = q ( p ( p q( p A = ( a a a q is the weight aay heefoe the non-quantitative index weight of decision aking unit nubeed in bluing opeation is: ( p ( p B AR ( a a a q = = = ( b b b p q q q( p Data Envelopent Calculation of Quantitative Weights Assue that X = x ( x x Y = ( y y ys stands fo the input and output vecto of the evaluation unit DMU i ( i nubeed i in which = and evey vecto coodinate is positive nube If ( v v vn u = ( u u v = u Means the weight vecto of the input and output then the linea pogaing odel can be deteined by Chanes-Coope tansfoation: s t ω X ax µ Y µ Y ω X = ω µ s n = Apply the data into this odel and the optial solution obtained is the accuately calculated quantitative index weigh Although the data esult fo data envelopent analysis ethod is oe obective and pesuasive it does not possess such peceptive cognition as excellent good qualified and unqualified and ebeship fo as in fuzzy copehensive evaluation As a esult the fuzzification of the esult by ebeship function is conducted in this aticle he opeation esult fo the data envelopent analysis can be egaded as the degee of ebeship of the coent set V = ( v v v p assuing that = ( p is the ebeship then: x ( p ( p ( + x p = p [ ] = p x < p p x < ( + p p B Substitute into the above equation and the B = ( b b b p degee of ebeship is 3 Copehensive evaluation Conduct copehensive evaluation of the above esult he copehensive evaluation atix is: B B R = = B k In which k eans the total nube of all indexes (quantitative and non-quantitative Suppose that A = ( a a a k = eans the weight then B = A and B B R B = ( a a a k = ( b b b p = B k Based on the axiu ebeship pinciple the final esult afte copehensive evaluation is 459

3 Jounal of heoetical and Applied Infoation echnology 8 th Febuay 3 Vol 48 No3 5-3 JAI & LLS All ights eseved ISSN: wwwatitog E-ISSN: B = ( b b b p and the axiu value is coesponding with the v ( v i in v v p 3 EVALUAION MODEL OF FUZZY NEURAL NEWORK RBF neual netwok [8 9] is able to siulate the patial adustent of the huan bain and eceive doain of utual coveage hee is no local iniu poble and it is easy and fast to lean with a high fitting pecision It can change the weight value of indexes in fuzzy copehensive evaluation odel aking it oe in line with the pactical situation he deteination of the index weight value is paticulaly ipotant in fuzzy copehensive evaluation odel 3 Intoduction of RBF neual netwok Radial Basis Function (RBF neual netwok is a kind of neual netwok put fowad by J Moody and C Daken in the late 98 s and a special b i thee-laye feed-fowad netwok with a single hidden laye As it siulates the neual netwok stuctue of the patial adustent and eceive doain of utual coveage in huan bain RBF is consideed to a local appoxiation netwok he stuctue of RBF neual netwok is a thee laye feed-fowad netwok siila to that of ultilaye feed-fowad netwok he fist laye is the input laye foed by signal souce oints; the second laye is hidden laye in which the nube of hidden units is dependent on the descibed poble and the tansfoation function of hidden units is RBF which is a daped nonlinea function but of cental and adial syety; the thid laye is the output laye esponding to the effect of input ode Because the apping of input to output is nonlinea and the apping of hidden laye space to output space is linea it can geatly acceleate the leaning speed and avoid the local iniu poble shown in Fig x h w x h w w y Output laye x n i Input laye h Hidden laye Fig Stuctue Chat RBF neual netwok is able to appoxiate any continuous function with abitay pecision and especially fit fo the classification poble he appoxiation chat is shown in Fig Obect u ( y( + y ( R B F Fig Appoxiation Chat 46

4 Jounal of heoetical and Applied Infoation echnology 8 th Febuay 3 Vol 48 No3 5-3 JAI & LLS All ights eseved ISSN: wwwatitog E-ISSN: Suppose that X = ( x x x n is the netwok s input and H = ( h h h is the base h vecto in adial diection in which eans the cente vecto of Gaussian function X C b h = e ( = and the nube C = ( c c cn node in netwok Base width vecto is B = ( b b b b and is the base width paaete of the node point Weight vecto is W = ( w w w and the output of the netwok in tie k : y ( = wh = w h + w h + + w o each an ideal output y( this aticle gets a pefoance index function as: E( = ( y( y( 3 Modeling Supposing that X = ( x x x is the netwok input then the nube of input is and the h nube of output and evaluation gade is n he connection weight between the second laye and the thid laye in the netwok w i is the weight value of the index in fuzzy copehensive evaluation odel he fist laye: the input laye As can be seen fo Fig the total nube of neuon in the input laye is so the input and output ae accodingly: I i = x i O i = x i i = = n he second laye: the hidden laye he evaluation gade of RBF neual netwok is n Judging fo Fig the hidden laye contains n neuon In this pape the evaluation gade is { A divided into fou levels: i } = {excellent good qualified unqualified } ie n = 4 heefoe fou paaetes a a a3 a4 ae needed fo the fou µ(x is fuzzy subsets Mebeship function pesented in the fo of tigonoetic function shown in Fig3 µ(x A A A3 A4 a a a 3 a 4 Fig3 Mebeship Function I i = O When the input is as i i = = n the hidden laye outputs the ebeship value of each level as follows: i O = A ( x i he thid level: the output level he output laye ainly conducts a copehensive evaluation of the input indexes he obtained evaluation gade and vecto ae: Input: 3 i O i I = 46

5 Jounal of heoetical and Applied Infoation echnology 8 th Febuay 3 Vol 48 No3 5-3 JAI & LLS All ights eseved ISSN: wwwatitog E-ISSN: Output: O 3 i = = w 3 Ii In which i = = n Yet RBF neual netwok has seveal shotcoings such as slow convegence ate and local iniu of enegy his aticle adopts a odified netwok and ipoves the connection weight of the netwok aking the weight value of the indexes in fuzzy neual netwok evaluation odel oe suitable fo pactical situation his pape calculates the output value by the evese of the netwok and gets the eo between the output value and the actual value hen coect the netwok s connection weight by the value obtained fo the fowad of the netwok which educes the netwok eo d p = t p y p Supposing the output eo is the eo function can be expessed as ep = ( t p y p In this aticle gadient descent ethod in RBF neual netwok leaning algoith is intoduced to aend the weight vecto W d aiing at educing p and inceasing the coputational accuacy he gadient descent ethod is shown in the following text: If w ( = w ( k + ηh ( y( y ( + α( w ( k w ( k w h b = ( y( y( and X C b 3 b ( = b ( k + η b + α( b ( k b ( k w c = ( y( y ( i hen x c i b ci ( = ci ( k + η ci + α( ci ( k ci ( k in which η eans the leaning speed and α eans oentu facto Based on Jacobean aay a final esult can be achieved: y( y ( = u( u( = w h c x b Supposing that W is the adusted value of W the iteative algoith foula of W based on gadient descent ethod is: W e = η + α W W ( n p ( n Pecede iteation utilizing the foula of W and end the netwok taining until the eo eet the equieents 33 Application Assue that the nube of evaluation indexes is and they ae A A A hese indexes coves all the copetition equieents fo Matial at athletes in outine copetition such as stength hyth style coodination content and stuctue etc Suppose that the nube of Matial at athletes taking pat in the copetition is n and they ae expessed as B B Bn If A = { A A A} and B = { B B Bn} thee eaches the following atix: B B B n A X X X n A X X X n In which A X X X n X i A < X < and i is the ebeship of the Matial at athlete unde index heefoe it X i can be concluded that when the value of is salle the athlete s level and ability unde this index is low copaably; and vice vese In this eseach the obtained ebeship unde each index is given a weight hen calculate the aveage of the weights he aveage value is consideed to be the final esult of the Matial at Wi X i Q = athlete that is i= Suppose that thee ae t efeees and evaluation gade is C C C Povide that the evaluation gade decease with the incease of index C i ie deceasing function Refeees would give an evaluation esult to each Matial at athlete in such way as the following: 46

6 Jounal of heoetical and Applied Infoation echnology 8 th Febuay 3 Vol 48 No3 5-3 JAI & LLS All ights eseved ISSN: wwwatitog E-ISSN: C C C A Q Q Q A Q Q Q A Q Q Q Accoding to national egulation the evaluation indexes ae classified into 8 goups in this pape as A A A8 and evaluation gade is divided into C C C 5 goups 5 as excellent good qualified unqualified and poo A Matial at Chapionships in cetain yea as a exaple this aticle eaches to the weight value of the eight evaluation indexes A A A8 ae espectively Select 6 Matial at athletes andoly and get the evaluation esults fo the efeees he pocessed esult is shown in able able Evaluation Result C C C 3 C 4 C 5 A 3 5 A 4 5 A A A A A 7 6 A 8 8 he evaluation atix of the evaluation indexes is: 3 4 R = Accoding to the calculation foula of fuzzy copehensive evaluation the final evaluation esult is: Q = A R = ( And A = ( As can be seen fo the above final evaluation esult 7% of the efeees conside the athlete s ability in this copetition to be excellent; 8% of the efeees conside the athlete s ability in this copetition to be good; 35% of the efeees conside the athlete s ability in this copetition to be qualified; 9% of the efeees conside the athlete s ability in this copetition to be unqualified; % of the efeees conside the athlete s ability in this copetition to be poo hen the final esult of this athlete can be deteined cobining the coesponding gade of the five evaluation gade Q = = Siilaly the othe five athletes final esults ae and 3 It can be seen fo the above analysis with the appeaance and developent of copute technology not only siulation and eulation of Matial at oveents but also analysis of oveent iage and data pocessing can be achieved by eans of copute As a esult the pefect cobination of Matial at and oden science and technology ethods has becoe one of the eseach hotspots about Matial at in ecent yea Copute siulation should conduct copehensive consideation as Matial at involves vaious fields such as body stuctue biology dynaics and kineatics Usually huan body is egaded as digitization odel of ultipaticle o ulti igid body In this eseach the acting foce aong diffeent pats of the huan body is taken as a facto affecting the outine 463

7 Jounal of heoetical and Applied Infoation echnology 8 th Febuay 3 Vol 48 No3 5-3 JAI & LLS All ights eseved ISSN: wwwatitog E-ISSN: pefoance And a digitized ulti igid body odel is foed with the digitization of the huan body Relative eseach wok can be conducted based on this odel accoding to the following siulated wokflow Fig4: Moveent of Matial at outine Digitization of ulti igid body odel Basic paaete Utility softwae Data pocessing Softwae Debugging Coputed esult Data pocessing Adust iage display Best Matial at oveent Fig4 Wokflow 4 CONCLUSIONS In the Matial at copetitions efeees give out each athlete s gade in a shot tie Obviously such esults contain abiguity which diectly affected the copetition fainess and ustness Whethe to the inheitance and developent of Matial at o to athletes own developent it is vey negative heefoe to design a fai scientific and ational ating syste is paticulaly ipotant his aticle constucts a fuzzy copehensive evaluation odel based on the theoy of fuzzy nubes Due to the high subectivity of this odel this eseach cobines RBF neual netwok odel and data envelopent analysis ethod with fuzzy copehensive evaluation odel and builds two kinds of evaluation odel as fuzzy data envelopent analysis and fuzzy neual netwok finally this odel enhances the eliability and scientificalness of this evaluation odel eaching a satisfactoy esult REFERENCES: [] Hao Dawei Zhang Wei Liu Chunhua SWO analysis of Chinese taditional Matial at Jounal of Xianning Univesity Vol3 No pp 3-4 [] Li Yan Dong Fei Copehensive eview on the design of the eulational syste of spots (atial at teaching Jounal of Shandong Institute of Physical Education and Spots Vol4 No9 8 pp [3] Liu Beixiang Yang Xiayuan Wang Dongei et al Application of Iage Measueent Data in Matial at echnique Analysis Jounal of Chengdu Spot Univesity Vol35 No4 9 pp 6-66 [4] Luo Minghua Fuzzy Matheatical Model fo Matial at Copetition Judges of Long Boxing Routines Matial at Science Vol5 No 8 pp 45-6 [5] Liu Jun Liu ongwei Fuzzy and Copehensive Evaluation Method on Pefoance Level of Routines in Copetitive Matial at Jounal of Shanghai Physical Education Institute Vol4 No4 pp 68-7 [6] Zhu Dong Application of Copute-aid aining to Matial at Routine Moveent Jounal of Shanghai Physical Education Institute Vol8 No3 4 pp

8 Jounal of heoetical and Applied Infoation echnology 8 th Febuay 3 Vol 48 No3 5-3 JAI & LLS All ights eseved ISSN: wwwatitog E-ISSN: [7] Jiao Baochong Zhao Yihuan Dong Liing Educational infoationization pefoance evaluation odel based on data envelopent analysis E-Education Reseach Vol4 7 pp 38-6 [8] Zhang Dingxue Liu Xinzhi Guan Zhihong Radial Basis Function Neual Netwok Algoith and Its Application Jounal of Petocheical Univesities Vol No3 7 pp [9] Qiao Junfei Han Honggui Optial Stuctue Design fo RBFNN Stuctue Acta Autoatica Sinica Vol36 No6 pp