DC Field | Value | Language |
---|---|---|
dc.contributor.author | Hong, S.G. | - |
dc.contributor.author | Kim, S.W. | - |
dc.contributor.author | Lee, Ju-Jang | - |
dc.date.accessioned | 2009-01-15T09:08:44Z | - |
dc.date.available | 2009-01-15T09:08:44Z | - |
dc.date.issued | 1995 | - |
dc.identifier.citation | Fuzzy Systems, 1995. International Joint Conference of the Fourth IEEE International Conference on Fuzzy Systems and The Second International Fuzzy Engineering Symposium., Proceedings of 1995 IEEE International Conference on, Volume: 4, On page(s): 1719-1726 | en |
dc.identifier.isbn | 0-7803-2461-7 | - |
dc.identifier.uri | http://hdl.handle.net/10203/8322 | - |
dc.description.abstract | Neural networks have been proposed as new computational tools for solving constrained optimization problems. In this paper the minimum cost path finding algorithm is proposed by using a Hopfield type neural network. In order to design a Hopfield type neural network, an energy function must be defined at first. To achieve this, the concept of a vector-represented network is used to describe the connected path. Through simulations, it will be shown that the proposed algorithm works very well in many cases. The local minima problem of a Hopfield type neural network is discussed | en |
dc.language.iso | en_US | en |
dc.publisher | IEEE | en |
dc.subject | Path finding | en |
dc.subject | Hopfield network | en |
dc.title | The Minimum Cost Path Finding Algorithm using a Hopfield Type Neural Network | en |
dc.type | Article | en |
dc.identifier.doi | 10.1109/FUZZY.1995.409914 | - |
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