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Title of Journal: Soft Comput

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Abbravation: Soft Computing

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Springer-Verlag

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10.1007/978-3-319-27140-8_43

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1433-7479

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A hilljump algorithm of Hopfield neural network f

Authors: RongLong Wang ShanShan Guo Kozo Okazaki
Publish Date: 2008/05/10
Volume: 13, Issue: 6, Pages: 551-558
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Abstract

In this paper we present a hilljump algorithm of the Hopfield neural network for the shortest path problem in communication networks where the goal is to find the shortest path from a starting node to an ending node The method is intended to provide a nearoptimum parallel algorithm for solving the shortest path problem To do this first the method uses the Hopfield neural network to get a path Because the neural network always falls into a local minimum the found path is usually not a shortest path To search the shortest path the method then helps the neural network jump from local minima of energy function by using another neural network built from a part of energy function of the problem The method is tested through simulating some randomly generated communication networks with the simulation results showing that the solution found by the proposed method is superior to that of the best existing neural network based algorithm

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