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Neural Networks

Authors

Arvind Chandrasekaran, Colorado Technical University, USA

Abstract

The neural networks review the categories, explaining the organization algorithm techniques required to improve the generalization performance and the Feedforward Neural Network (FNN) learning speed. They are needed to discover the research trends changes under the six categories of the optimization algorithms for the learning rate, learning algorithms which are gradient-free. Metaheuristic algorithms collectively and new research directions are recommended for the researchers to facilitate the algorithm's understanding of the natural world applications to solve the complex engineering, management, and problems in the health sciences. FNN gained research attention for making an informed decision. The literature survey focuses on optimization technology and learning algorithms. The optimization techniques and the FNN learning algorithms identified are segregated into six categories based on the mathematical model, problem identification, proposed solution, and technical reasoning. FNN contributions rapidly increase the ability to make informed decisions reliably.

Keywords

Classification schemes; Optimization techniques; CNN-RNN Model;