Evaluation model of young basketball players physical quality and basic technique based on rbf neural network

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1 ISSN : Volume 8 Issue 9 BoTechology BoTechology A Ida Joural Evaluato model of youg basketball players physcal qualty ad basc techque based o rbf eural etwork Guag Lu Wuha Isttute Of Physcal Educato, Wuha , Hube, (CHINA) E-mal: @qq.com BTAIJ, 8(9), 013 [ ] ABSTRACT I order to coduct comprehesve udgmet o youg basketball players physcal qualty ad basc techque scetfcally ad systemcally, ths study establshes the combato evaluato model of youg basketball players physcal qualty ad basc techque, uses fuzzy aalytc herarchy process to determe the weght of each level dcator ad calculate the combato weghts of the lowest level dcators, ad carres through a comprehesve evaluato of the dfferet youg basketball players physcal qualty ad basc techque usg Topss method. The evaluato results truly reflect the comprehesve stuato of every athlete, ad the use of the dcators the evaluato model to establsh the RBF eural etwork model makg the evaluato modeled. Ths model provdes a ew dea for the comprehesve evaluato of youg basketball players physcal qualty ad basc techque, ad s coducve to the tmely motorg ad regulato o trag for coaches ad youg basketball players. 013 Trade Scece Ic. - INDIA KEYWORDS Fuzzy aalytc herarchy process; Basketball player; Physcal qualty; Neural etwork model. INTRODUCTION At preset, may researches have bee carred through o physcal qualty ad basc techques for youg athletes, but the research are maly about the athlete s body shape, specal achevemets ad game results, ad most of them are elaborate macro theory. Comprehesve evaluato model for physcal qualty ad basc techque s much less. Yu Shao-yog coducted research o 1 youg basketball players physcal dcators usg prcpal compoet aalyss ad cluster aalyss, obtaed the rakg of the qualty dcators; Yag Fe descrbed the selecto dcators of teeage basketball players a macroscopc scale Schua Provce; Zhag Bo compared ad aalyzed the test scores of youg basketball players physcal qualty ad basc techque. I the research of evaluato model of youth basketball players physcal qualty ad techcal dcators, the dcators used by the researchers are ot the same, ad the weght of each dex are mostly determed through experece, whch s lack of certa scetfc. Ths study plas to use fuzzy aalytc herarchy process ad TOPSIS tegrated evaluato method to establsh the combato evaluato model o youth basketball players physcal qualty ad basc techque, uses fuzzy aalytc herarchy process to determe the weghts of dcators at all levels ad calculate the comb-

2 1194 Evaluato model of youg basketball players physcal qualty BTAIJ, 8(9) 013 ato weghts of the bottom dcators, ad coducts comprehesve evaluato of dfferet youth basketball players physcal qualty ad basc techques usg Topss method. Ths model provdes a ew way of thkg for the youg basketball players physcal qualty ad basc techque, ad s coducve to the tmely adustmet of basketball athletes trag. BRIEF INTRODUCTION OF FUZZY ANA- LYTIC HIERARCHY PROCESS The realzato of ths work supposes the avalablty of a great umber of repettos of samples respodg to the same kow theoretcal model. I practce, as the theoretcal model s ukow, we use the Mote- Carlo method based o the geerato of the data by computer accordg to a fxed theoretcal model. Fuzzy aalytc herarchy process s put forward order to make up for the dffculty ad u-scetfcally of tradtoal aalytc herarchy process testg the cosstecy of udgmet matrx. Fuzzy aalytc herarchy process s a system aalyss method of qualtatve aalyss ad quattatve aalyss, the prcples of whch are bascally the same wth that of AHP. The basc step of fuzzy aalytc herarchy process s smlar to that of tradtoal aalytc herarchy process, show as follows: Costruct a multlayer herarchcal structure ad form a target tree dagram, as show Fgure 1. Fgure 1 : Model structure of fuzzy aalytc herarchy process Buld a fuzzy cosstet matrx: R stads for the fuzzy cosstet udgmet matrx. Frstly, select certa factor the upper layer ad determe the dexes that are related to the factor, from the lower layer. The compare the relatve mportace of dexes the lower layer. Suppose that a upper layer dexes ca be explaed by dexes a 1, a,, a from the ext layer, ad the a fuzzy cosstet udgmet matrx ca be bult, as show BoTechology A Ida Joural TABLE 1. TABLE 1 : Fuzzy cosstet udgmet matrx C a 1 a a a 1 r 11 r 1 r 1 a r 1 r r a r 1 r r I TABLE 1, ( 1,,, ; 1,,, ) meas the r relatve mportace of dex a, the umber dex from upper factor C, ad dex a, the umber dex from the same upper factor C. I order to quatfy the cocept of mportace, the followg evaluato stadard ca be used, show TABLE. I accordace wth the evaluato method TABLE, after par wse comparso of the evaluato dexes of factor C,, a fuzzy udgmet matrx ca be obtaed: r11 r1 R r 1 (1) r () r (3) r r1 r1 r r r r The matrx has the followg three propertes: 0.5, 1,,, ; 1 r r k r,, 1,,, ; k,,, k 1,,,. Calculate the weght of each dex: Suppose the weght set of dexes a, a,, a 1 s W ( 1,,, ), the: r 0.5 a( ),,1,,, I the above formula 0 a 0.5, a s the evaluator s measure of the degree of dfferece betwee the proposed evaluato obects. Whe R s cosstet, the above formula s ot strctly true. The weght vector W ( 1,,, ) ca be determed by the least squares prcple, show formula (1): m s. t. z , [ 0.5 a ( 0, (1 ) ) r ] Accordg to Lagrage s theorem, the above formula ad the formula below are equvalet. m L (, ) [ 0.5 a ( ) r ] ( I the formula s the Lagrage multpler. 1) (1)

3 BTAIJ, 8(9) 013 Guag Lu 1195 Importace scale r TABLE : Evaluato stadard for fuzzy aalytc herarchy process Degree of relatve mportace Explaato 0.5 Equally mportat The two elemets compared are equally mportat 0.6 Slghtly mportat Wth the two elemets compared, the mportace of oe elemet s slghtly hgher tha the other 0.7 Absolutely mportat Wth the two elemets compared, the mportace of oe elemet s apparetly hgher tha the other 0.8 Really mportat Wth the two elemets compared, the mportace of oe elemet s sgfcatly hgher tha the other 0.9 Absolutely mportat Wth the two elemets compared, the mportace of oe elemet s extremely hgher tha the other 0.1,0.,0.3,0.4 Coverse comparso If the mportace degree rato of dex a to dex a s r, the the mportace degree rato of dex a to dex a s r 1 r Calculate partal dervatves of m L(, ) about ( 1,,, ) ad supposg that value of s zero, the followg equato set ca be obtaed: a [ 0.5 a ( ) r ] a [0.5 a ( r ] 0 1 k 1 ( 1,,, ) () The above equato set s equvalet to the followg equato set: k k Radal Bass Fucto eural etwork (Radal Bass Fucto, RBF) s a eural etwork proposed by J. Moody ad C. Darke the late 1980s. It s a kd of fucto takg the dstace to the fxed pot as the depedet varables. RBF etwork s a three-layer structure, respectvely the put layer, hdde layer ad output layer. The typcal three-layer structure of RBF etwork topology s show Fgure : 1 [ a ( ) a ( r r ) 0 ( 1,,, ) (3) The umber of ukows ths equato set s +1,.e.,,,, ad the umber of equatos s +1, 1 a ( 1) 1 a a 3 a a ( r1 r 1 ) 1 a 1 a ( 1) a 3 a a ( r r ) 1 a ( 1) 1 a a 3 a a ( r r ) Solve the equato set (4) ad weght of each evaluato dex ca be determed. Calculate the combato weght C of the bottom layer dexes weghtg method. C =dex weght of layer B*dex weght of layer C. (4) INTRODUCTION OF RBF NEURAL NET- WORK MODEL Fgure : RBF etwork structure topologcal graph I Spkg eural etwork, a spke euro correspods to a collecto of euros recevg a pluralty of sgals from the upper euro the momet oft, where, X s o behalf of the put layer, Q s represetatve of the hdde layer, ad F represets the output layer. Assumes that k wm s the coecto weghts of euro m s syapse k wth euro, k d s the delay of the syaptc k. The weghts calculato method usg RBF eural etwork s show as follows: w k w k 1 yk ym kh w k 1 w k (5) X C b y k y m k w h 3 (6) b BoTechology A Ida Joural

4 1196 Evaluato model of youg basketball players physcal qualty BTAIJ, 8(9) BoTechology BoTechology A Ida Joural b k b k b b k b k (7) x c c y k ym k w b (8) c k c k 1 c c k 1 c k (9) Substtuted to the Spkg pulse sgal to adust weght, t mproves the respose speed of the etwork, the more ts regulato ablty of the eural etwork s more stroger, whch ca be adapted to the stuato where tal weghts are u-deal, at the same tme learg speed s much faster. ESTABLISHMENT OF THE YOUTH BAS- KETBALL PLAYERS PHYSICAL FITNESS AND BASIC TECHNIQUE S EVALUATION SYSTEM Through a large umber of documet lterature ad cosultg basketball seor experts, ths paper falzes the evaluato dexes of Youth Basketball Players physcal qualty ad basc techque, ultmately establshes a three-ter herarchcal structure, uses fuzzy evaluato method by costructg udgmet matrx of parwse comparso, ad determes the weght of each layer s dcators ad the combato weghts of the lowest level dcator; the results are show TABLE 3-7. TABLE 3 : Comprehesve evaluato system of youg basketball players physcal qualty ad basc techque Frst layer dex Comprehesve qualty A Secodary layer Physcal qualty B1 Basc techque B Three-layer dex 100m ru C1 5.8m*6 shuttle ru C Stadg log ump C3 Ru-up hop touch heght C4 mult-group ptch shuttle ru C5 body precursor C6 90s the reboudg ablty C7 Overall pass ad lay-up ball C8 comprehesve drbble C9 The backsldg defesve C10 The comprehesve level evaluato model of youg basketball player s show TABLE 7. Through assessg the 3 Youg Basketball Play- TABLE 4 : Fuzzy cosstet matrx of the frst layer dexes A B1 B weght B B TABLE 5 : Fuzzy cosstet matrx of the secod layer dexes (physcal qualty) B1 C1 C C3 C4 C5 C6 weght C C C C C C TABLE 6 : Fuzzy cosstet matrx of the secod layer dexes (basc techque) B C7 C8 C9 C10 weght C C C C TABLE 7 : Comprehesve Evaluato Model of Youg Basketball Players Physcal Qualty ad basc techque Frst layer dex Comprehesve qualty A Secodary layer Physcal qualty B1 Basc techque B Three-layer dex Combato weght 100m ru C m*6 shuttle ru C Stadg log ump C3 Ru-up hop touch heght C4 mult-group ptch shuttle ru C5 body precursor C6 90s the reboudg ablty C7 Overall pass ad lay-up ball C8 comprehesve drbble C9 The backsldg defesve C ers, the results of each perso are show TABLE 8. Accordg to the formula, coduct stadardzed trasformato o each dex; the results are show TABLE 9. Accordg to the results TABLE 9, the postve deal soluto ad egatve deal soluto are:

5 BTAIJ, 8(9) 013 Guag Lu 1197 Z Z + - TABLE 8 : The three Youg Basketball Players varous accomplshmets Team member C1 C C3 C4 C5 C6 C7 C8 C9 C TABLE 9 : The ormalzed values of 3 Youg Basketball Players varous performaces Team member C1 C C3 C4 C5 C6 C7 C8 C9 C (0.58,0.6,0.6,0.6,0.59,0.63,0.68,0.6,0.6,0.6) (0.57,0.56,0.56,0.56,0.57,0.54,0.46,0.56,0.53,0.53) See from TABLE 8, by Fuzzy AHP determe the combato weghts set of each evaluato dex s W = (0.1, 0.1, 0.07, 0.1, 0.09, 0.05, 0.1, 0.16, 0.1, 0.07). Accordg to Equatos 13 ad 14, calculate the weghted Eucldea dstace C of postve deal soluto ad egatve deal soluto, ad use formula 15 to calculate the relatve closeess, the results are show TABLE 10. TABLE 10 : The closeess ad sort of the athletes ad the postve deal soluto Team member + D - D C Sort Fgure 3 : RBF eural etwork error codto The three me s basketball players are sorted accordg to the relatve closeess reflectg the dffereces the overall qualty of the athletes. Accordg to the above dcators ad ther weghts, usg SPSS17.0 statstcal software to buld a radal bass fucto eural etwork model, the model s error s show Fgure 3. Fgure 3 shows that the model s error s very small dcatg that the evaluato ablty of the model s superor. CONCLUSIONS Ths study uses fuzzy aalytc herarchy process ad TOPSIS method to establsh a comprehesve evaluato model of youg basketball players physcal qualty ad basc techque, substtute the dcators of three teeager me basketball players physcal qualty ad basc techque to the model, ad obtas the comprehesve rakg of each athletes. The fuzzy aalytc herarchy process the combed model s used to determe the evaluato dex weght. O ths bass t uses Topss comprehesve evaluato method to coduct comprehesve evaluato o each obect to be evaluated. The udgmet result s more obectve ad reasoable tha the tradtoal method. The RBF eural etwork model establshed accordg to varous dcators ad ther weghts, the error s small, ad the evaluato performace s superor. The evaluato model ca be used for the evaluato of youg basketball players physcal qualty, ca also be exteded to the evaluato of other athletes qualty, ad has broad applcato prospects ad hgher applcato value. REFERENCES [1] A.Delorme, S.J.Thorpe; Spke NET: a Evet- BoTechology A Ida Joural

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