Genetic optimization of classical neural networks - Nawrocka, Monika
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Neural networks and genetic algorithms are methods of solution of optimization problems. It consists of determining the best solution to the problem among acceptable solutions due to the criterion of quality. By combining genetic algorithms with neural network models, is obtained the genetic neural network (GNN) in the concept of optimization of processes or events. Optimization in terms of the genetic algorithms is based on the methods of natural selection. The algorithm activity consists in converting the genetic population in accordance with the multidirectional search of potential…mehr

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Produktbeschreibung
Neural networks and genetic algorithms are methods of solution of optimization problems. It consists of determining the best solution to the problem among acceptable solutions due to the criterion of quality. By combining genetic algorithms with neural network models, is obtained the genetic neural network (GNN) in the concept of optimization of processes or events. Optimization in terms of the genetic algorithms is based on the methods of natural selection. The algorithm activity consists in converting the genetic population in accordance with the multidirectional search of potential solutions to a given problem. It operates on the chromosomes and its role has the fixed-length vector consisting of the binary values.
Autorenporträt
The book's author is a graduate of economics with specialization in information systems at The Catholic University of Lublin. Currently, Monika Nawrocka is a PhD student at The Jerzy Kukuczka Academy of Physical Educationn. She specializes in quantitative prediction and optimization methods.