期刊
EXPERT SYSTEMS WITH APPLICATIONS
卷 37, 期 7, 页码 5331-5335出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.eswa.2010.01.002
关键词
Data transformation techniques (DTT); Hopfield neural networks (HNN); Travelling salesman problem (TSP)
This study presents an improved artificial neural network (ANN) approach for solving travelling salesman problem (TSP). We employ Hopfield neural networks (HNN) and data transformation techniques (DTT) together to improve accuracy of the results and reach to the optimal tours with less total distances. To meet this purpose we integrate Z-score and logarithmic approaches with Hopfield neural networks, i.e., we prepare more appropriate inputs for the ANN training process. Then we evaluate the usefulness of our integrated approach by applying it on the 10-city problem which has been used for comparison by several authors. Results show that our integrated approach gives better results than basic Hopfield approach. In the other hand Z-score based approach gives the best results among all, logarithm based approach takes the second place and basic approach takes the third place. (C) 2010 Elsevier Ltd. All rights reserved.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据