Learning in multilayer perceptrons using global optimization strategies.

DOI10.1016/S0362-546X(01)00459-XzbMath1042.90653OpenAlexW2008624297WikidataQ127628744 ScholiaQ127628744MaRDI QIDQ1875372

George D. Magoulas, Michael N. Vrahatis, Vassilis P. Plagianakos

Publication date: 26 August 2004

Published in: Nonlinear Analysis. Theory, Methods \& Applications. Series A: Theory and Methods (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/s0362-546x(01)00459-x

Mathematics Subject Classification ID

Applications of mathematical programming (90C90) Approximation methods and heuristics in mathematical programming (90C59) Neural networks for/in biological studies, artificial life and related topics (92B20)

Related Items (4)

Global optimization issues in deep network regression: an overview ⋮ An application of interval-valued neural networks to a regression problem ⋮ Improved sign-based learning algorithm derived by the composite nonlinear Jacobi process ⋮ APPROACHES TO ADAPTIVE STOCHASTIC SEARCH BASED ON THE NONEXTENSIVE q-DISTRIBUTION

Uses Software

• GAToolBox

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