Dissertation/Thesis Abstract

A study of cell-based genetic algorithms with applications to neural networks
by Dinh, Hoa, M.S., California State University, Long Beach, 2013, 62; 1527480
Abstract (Summary)

In the past few decades, Genetic Algorithms (GA) and Artificial Neural Networks (ANN) have been widely used in various fields, such as data processing, robotics and pattern recognition. In particular, GA is used in optimization problems for which there is no known tractable algorithm for finding solutions, while ANN is used mainly in classification or regression problems. To improve the effectiveness of ANN, scientists proposed methods of combining GA and ANN. While most previous approaches apply GA to obtain the structure or the initial weights of an ANN, this thesis explores the cellbased GA model and its application in training an ANN as part of a supervised-learning task.

Indexing (document details)
Advisor: Elbert, Todd
School: California State University, Long Beach
School Location: United States -- California
Source: MAI 52/05M(E), Masters Abstracts International
Subjects: Computer Engineering, Computer science
Keywords: Mutations, Neurons
Publication Number: 1527480
ISBN: 978-1-303-77373-0
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