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Using Improved Genetic Algorithm to Solve Real Eigenvalue of Matrix

Xianghu Liu

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Abstract

This paper based on the distribution about eigenvalue of matrix,firstly,determinate the approximately distributed region of real matrix eigenvalue,then by using genetic algorithm,with real value encoding and adaptive crossover and mutation probabilities to solve approximate real eigenvalue of matrix.Simulation results show that this algorithm can reach a certain precision,has a certain versatility,and give a rapid method to solve eigenvalue of matrix.

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What this paper is about

This paper based on the distribution about eigenvalue of matrix,firstly,determinate the approximately distributed region of real matrix eigenvalue,then by using genetic algorithm,with real value encoding and adaptive crossover and mutation probabilities to solve approximate real eigenvalue of matrix.Simulation results show that this algorithm can reach a certain precision,has a certain versatility,and give a rapid method to solve eigenvalue of matrix.

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Available abstract

This paper based on the distribution about eigenvalue of matrix,firstly,determinate the approximately distributed region of real matrix eigenvalue,then by using genetic algorithm,with real value encoding and adaptive crossover and mutation probabilities to solve approximate real eigenvalue of matrix.Simulation results show that this algorithm can reach a certain precision,has a certain versatility,and give a rapid method to solve eigenvalue of matrix.

Key concepts: Eigenvalues and eigenvectors, Crossover, Matrix (chemical analysis), Divide-and-conquer eigenvalue algorithm, Eigenvalue algorithm, Algorithm, Generalized eigenvector, Genetic algorithm

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