E·voiution of Topology and Wei,ght-s. of Neural Netwo·rks. Using.Semi Genetic Operators

Abstract

Evolutionary·co.nipimit'iQo  is  a· c'!a s of glbbal ·searb  techniq

based on the lei.lffi:ing process ,of  g po_pl)'latiog-·of pote.n:tiaf solutions to

a  ven probl_e-ID'.  thahas .been  succe_ssfull'y  applied    19  v ety of

prQblern, lll thls paper a riew approach  to. design lie_ ural ne'twQj:ks

based oh ev.ohltipnary -computa.tio.rt i·s pre.Seri-L  _A   tine-f.!£ clurP.mosome

'repr:esentati:on  or the etwor}< i_s.  u_secl: 'Q.y  genetiC  gperntb_l:s, whicQ

allow th¢  voJution of.the   chitecture and' weight-s ·simMltaneousfy

without the ne¢d : tlocal Â·-v.:e!gh_t-s· opthnization. Dii$ , paper - d- cribes

.t he approach, the" o.per HQ(S and rep 'H:tS  r  \llt$  '()[the a}Jplicati:on :Qf

this te6hnique-.to- ;;everal  biAal)l cl'iissifi·cation prob eros