' w" S, p6 L ] ia=max(p'); %#ok<UDIM>0 \# h' l$ S' ^. c( h
for i=1:145 p, c: C$ F {, F6 m( ~/ C! B
for j=1:3 5 N; r, p: S+ d5 qptest(i,j)=p(i,j)/a(i); ; v' _' I" Z$ G( p1 d
end ' A# A$ G) H8 i0 t% ?1 h xend 2 e4 @9 A& |- h7 ~0 L5 U; C2 r 2 P: n! V" W( { [. L+ l: E6 k. F 1 B7 V5 l: ]- ]p1=ones(1,14);; _% m; M! O, J9 Y, N9 g
p2=0.8.*ones(1,14);" O% b. O @, O$ x2 A
p3=0.6.*ones(1,14);& M8 d6 |+ @# L8 X
p4=0.4.*ones(1,14);1 n. ~, c8 Y; y
p5=0.2.*ones(1,14); ~! y X/ I2 H5 M
p6=0.*ones(1,14);. |1 I7 |& L6 q# M h/ H7 E, V
ptrain=[pl;p2;p3;p4;p5;p6]; ) l$ b6 z" r8 H1 w. vt=[100,80,60,40,20,0];" T# |$ [! Z) l+ c" X
: r6 c8 }$ I* a* ^ ) X' t+ |" {* G7 Knet=newff(minmax(ptrain'),[59,1],{tansig','purelin'},traingd');5 I0 E% x# M$ @1 `* c* x2 E. Z, O
net=init(net); " I _' N% _9 G9 znet.trainparam.epochs=100000;, Y: F: M# \: t* k: m$ m. Z+ r
net.trainparam.goal=1e-10; * u" u+ a) r# \8 V2 C) y[net,tr]=train(net,ptrain',t);: S$ U' F9 V4 h+ _' X
( ^& q" @; f, A( X( C* ]+ m: m1 L- h6 [4 y( O; Y0 y6 `8 X
for i=1:3. D2 o0 ]' i' r u4 ^
a=ptes(:,i);9 m- V, z, F; k0 n y; j& X$ o, V
score(i)=sim(net,a); %#ok<SAGROW> 8 M+ r0 y+ R& V1 W1 Eend9 z7 h' f* _9 y; V