C++ Neural Networks and Fuzzy Logic: Preface


C++ Neural Networks and Fuzzy Logic



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C neural networks and fuzzy logic

C++ Neural Networks and Fuzzy Logic

by Valluru B. Rao

MTBooks, IDG Books Worldwide, Inc.



ISBN: 1558515526   Pub Date: 06/01/95

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Performance of the Hopfield Network

Let us now look at Hopfield and Tank’s approach at solving the TSP.



Hopfield and Tank Example

The Hopfield network’s use in solving the traveling salesperson problem is a pioneering effort in the use of

the neural network approach for this problem. Hopfield and Tank’s example is for a problem with 10 cities.

The parameters used were, A

1

= 500, A



2

 = 500, A

3

 = 200, A



4

 = 500, Ä = 1, » = 50, and m = 15. A good solution

corresponding to a local minimum for E is the expected, if not the best, solution (global minimum). An

annealing process could be considered to move out of any local minimum. As was mentioned before, the

traveling salesperson problem is one of those problems for which a single approach cannot be found that will

be successful in all cases. There isn’t very much guidance as to how to choose the parameters in general for

the use of the Hopfield network to solve the traveling salesperson problem.


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