Autors: Mladenov, V. M., Maratos, N.
Title: Neural Networks for Solving Constrained Optimization Problems
Keywords: neural networks, constrained optimization, penalty function

Abstract: In this paper we consider several Neural Network architectures for solving constrained optimization problems with inequality constrains. We present a new architecture based on the exact penalty function approach. Simulation results based on SIMULINK® models are given and compared.

References

    Issue

    4th International Multiconference on Circuits, Systems, Computers and Communications CSCC 2000, pp. 1351-1359, 2000, Greece, WSEAS PRESS

    Цитирания (Citation/s):
    1. Begashaw, N., Comert, G. and Medhin, N.G., 2023. “Modeling Covid-19 Epidemic with Quarantine and Lockdown and Analysis,” Dynamic Systems and Applications, vol. 32, issue (1). ISSN: 1056-2176, pp. 275 - 293 (Google Scholar) - 2023 - от чужди автори в чужди издания, неиндексирани в Scopus или Web of Science
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    Вид: пленарен доклад в международен форум, индексирана в Google Scholar