计算机应用研究2016，Vol.33Issue(11)：3391-3395,5.DOI:10.3969/j.issn.1001--3695.2016.11.042
一种并行模糊神经网络最短路径算法
Parallel fuzzy neural network shortest path algorithm
摘要
Abstract
This paper proposed a parallel fuzzy neural network shortest path (PFNNSP)algorithm to solve the expected shor-test path problem on fuzzy network.First,it defined the definition of fuzzy network’s expected shortest path problem.Next, PFNNSP algorithm combined fuzzy simulation was developed to estimate edges’length.In the PFNNP,the pulse wave spread in parallel between neurons and searched shortest path of any pair nodes,while the shortest path and path length were obtained with the use of backtrack.Experiments on datasets with different scales show that the proposed PFNNSP algorithm leads to shorter computing time when compared with the well-known Dijkstra algorithm and A* algorithm.关键词
并行模糊神经网络最短路径/模糊模拟/神经元/脉冲Key words
PFNNSP/fuzzy simulation/neuron/pulse分类
信息技术与安全科学引用本文复制引用
闫春望,黄玮,王劲松..一种并行模糊神经网络最短路径算法[J].计算机应用研究,2016,33(11):3391-3395,5.基金项目
国家自然科学基金资助项目（61301140，61272450，61673295）；天津市教委科研计划资助项目（20120703）；天津市科技支撑资助项目 （）
