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2000•Journal of Wuhan Yejin University of Science and TechnologyRequires access

Hybrid Computation Intelligent Learning Algorithm of Global Convergence for BP Neural Network Based on Genetic Algorithm

Xiong Ling

Open publisher page 3 citations

Abstract

In this paper, a hybrid computation intelligent learning algorithm with the global convergence that combines BP algorithm with genetic algorithm is proposed. Since this algorithm integrates the advantages of BP algorithm and genetic algorithm, it has a better convergence property and the times of global search decrease significantly. The results of computer simulations show that this algorithm is obviously more excellent than genetic algorithm or BP algorithm.

About this research paper

What this paper is about

In this paper, a hybrid computation intelligent learning algorithm with the global convergence that combines BP algorithm with genetic algorithm is proposed. Since this algorithm integrates the advantages of BP algorithm and genetic algorithm, it has a better convergence property and the times of global search decrease significantly. The results of computer simulations show that this algorithm is obviously more excellent than genetic algorithm or BP algorithm.

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OpenAlex reports 3 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

In this paper, a hybrid computation intelligent learning algorithm with the global convergence that combines BP algorithm with genetic algorithm is proposed. Since this algorithm integrates the advantages of BP algorithm and genetic algorithm, it has a better convergence property and the times of global search decrease significantly. The results of computer simulations show that this algorithm is obviously more excellent than genetic algorithm or BP algorithm.

Key concepts: Algorithm, Population-based incremental learning, Convergence (economics), Genetic algorithm, Cultural algorithm, Computation, Computer science, Artificial neural network

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