Publicação: Implementation of two-stage Hopfield model and its application in nonlinear systems
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2004-01-01
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Springer
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This paper presents an efficient neural network for solving constrained nonlinear optimization problems. More specifically, a two-stage neural network architecture is developed and its internal parameters are computed using the valid-subspace technique. The main advantage of the developed network is that it treats optimization and constraint terms in different stages with no interference with each other. Moreover, the proposed approach does not require specification of penalty or weighting parameters for its initialization.
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Artificial Intelligence and Soft Computing - Icaisc 2004. Berlin: Springer-verlag Berlin, v. 3070, p. 954-959, 2004.
