Amanote Research

Amanote Research

    RegisterSign In

Recurrent Neural Approach for Solving Several Types of Optimization Problems

doi 10.5772/5544
Full Text
Open PDF
Abstract

Available in full text

Date

September 1, 2008

Authors
Ivan N. da SilvaWagner C.Lucia V.Rogerio A.
Publisher

InTech


Related search

Global Exponential Stability of Recurrent Neural Networks for Solving Optimization and Related Problems

IEEE Transactions on Neural Networks
2000English

Neural Network Approach for Solving Inverse Problems

English

Applications of Recurrent Neural Networks to Optimization Problems

2008English

A Hybrid Approach for Solving Dynamic Bi-Level Optimization Problems

Computacion y Sistemas
Computer Science
2018English

Neural Network Approach for Solving Singular Convex Optimization With Bounded Variables

Open Journal of Applied Sciences
2013English

An Efficient Quantum Multiverse Optimization Algorithm for Solving Optimization Problems

International Journal of Advances in Applied Sciences
2020English

Neural Networks for Constrained Optimization Problems

International Journal of Circuit Theory and Applications
Electronic EngineeringOpticalApplied MathematicsComputer Science ApplicationsElectricalMagnetic MaterialsElectronic
1993English

Structured Clanning-Based Ensemble Optimization Algorithm: A Novel Approach for Solving Complex Numerical Problems

Modelling and Simulation in Engineering
ModelingEngineeringComputer Science ApplicationsSimulation
2018English

Design of Artificial Neural Network for Solving Inverse Problems

Journal of Al-Nahrain University Science
2007English

Amanote Research

Note-taking for researchers

Follow Amanote

© 2025 Amaplex Software S.P.R.L. All rights reserved.

Privacy PolicyRefund Policy