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| Artículos de revistas
Neural approach for solving several types of optimization problems
| dc.creator | da Silva, IN | |
| dc.creator | Amaral, WC | |
| dc.creator | Arruda, LVR | |
| dc.date | 2006 | |
| dc.date | MAR | |
| dc.date | 2014-11-18T12:07:28Z | |
| dc.date | 2015-11-26T17:50:07Z | |
| dc.date | 2014-11-18T12:07:28Z | |
| dc.date | 2015-11-26T17:50:07Z | |
| dc.date.accessioned | 2018-03-29T00:33:17Z | |
| dc.date.available | 2018-03-29T00:33:17Z | |
| dc.identifier | Journal Of Optimization Theory And Applications. Springer/plenum Publishers, v. 128, n. 3, n. 563, n. 580, 2006. | |
| dc.identifier | 0022-3239 | |
| dc.identifier | WOS:000241554100005 | |
| dc.identifier | 10.1007/s10957-006-9032-9 | |
| dc.identifier | http://www.repositorio.unicamp.br/jspui/handle/REPOSIP/65265 | |
| dc.identifier | http://www.repositorio.unicamp.br/handle/REPOSIP/65265 | |
| dc.identifier | http://repositorio.unicamp.br/jspui/handle/REPOSIP/65265 | |
| dc.identifier.uri | http://repositorioslatinoamericanos.uchile.cl/handle/2250/1289585 | |
| dc.description | Neural networks consist of highly interconnected and parallel nonlinear processing elements that are shown to be extremely effective in computation. This paper presents an architecture of recurrent neural net-works that can be used to solve several classes of optimization problems. More specifically, a modified Hopfield network is developed and its inter-nal parameters are computed explicitly using the valid-subspace technique. These parameters guarantee the convergence of the network to the equilibrium points, which represent a solution of the problem considered. The problems that can be treated by the proposed approach include combinatorial optimiza-tion problems, dynamic programming problems, and nonlinear optimization problems. | |
| dc.description | 128 | |
| dc.description | 3 | |
| dc.description | 563 | |
| dc.description | 580 | |
| dc.language | en | |
| dc.publisher | Springer/plenum Publishers | |
| dc.publisher | New York | |
| dc.publisher | EUA | |
| dc.relation | Journal Of Optimization Theory And Applications | |
| dc.relation | J. Optim. Theory Appl. | |
| dc.rights | fechado | |
| dc.rights | http://www.springer.com/open+access/authors+rights?SGWID=0-176704-12-683201-0 | |
| dc.source | Web of Science | |
| dc.subject | recurrent neural networks | |
| dc.subject | nonlinear optimization | |
| dc.subject | dynamic programming | |
| dc.subject | combinatorial optimization | |
| dc.subject | Hopfield network | |
| dc.title | Neural approach for solving several types of optimization problems | |
| dc.type | Artículos de revistas |