The capture forecast problem of anchovy in the northern part of Chile traditionally has been
shaped utilizing classical lineal decline (RLC). Nevertheless, the technique of RLC does not
consider the not lineal phenomenon that can exhibit the process of forecast. Therefore, in
this memory of title is proposed a not lineal model of prediction of capture of anchovy based
on networks neural sigmoidal (RNS). The architecture of the model RNS is composed by an
input layer, a not lineal hidden layer and the output lineal layer and the weights of the RNS …

< p> El&nbsp; problema&nbsp; de&nbsp; pron&oacute; stico&nbsp; de&nbsp;
captura&nbsp; de&nbsp; anchovetas&nbsp; en&nbsp; la&nbsp; zona&nbsp; norte&nbsp;
de&nbsp; Chile tradicionalmente ha sido modelado utilizando regresi&oacute; n lineal
cl&aacute; sica (RLC). Sin embargo, la t&eacute; cnica&nbsp; de&nbsp; RLC&nbsp;
no&nbsp; considera&nbsp; los&nbsp; fen&oacute; menos&nbsp; no&nbsp; lineales&nbsp;
que&nbsp; puede&nbsp; exhibir&nbsp; el&nbsp; proceso&nbsp; de pron&oacute; stico …