볼록 다각형을 이용한 자기조직화 신경망의 연결강도 초기화와 유클리디안 외판원 문제의 적용

Abstract

This paper provides a new method of initializing neurons used in self-organizing neural networks and sequencing of input nodes. We use a general property that in any optimal solution for euclidean travelling salesman problem, vertices located on the convex hull are visited in the order in which they appear on the convex hull boundary. We composite input nodes as number of convex hulls and initialize neurons as shape of external convex hull. As a result of our experiment, we obtain more improved solutions and these solutions can be used for initial solutions of any global search algorithms.