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To solve the problem which is hard to avoid the local optimal solution or slower population diversity when using genetic algorithm to generate the fuzzy rules in a fuzzy system, this paper proposes an automatic rule generation using fuzzy genetic algorithm. This algorithm utilizes the rules population diversity and evolutionary speed to automatically adjust the crossover rate and mutation rate based...
The genetic algorithm is a self-adapting probabilistic iterated search method, which is based on a principle of the natural choice and the natural genetic mechanisms. And it can simulate the development law of biological evolution in the natural world and can be used in the complex nonlinear optimization problems in continuous variables and discrete variables mixed.This paper uses the genetic algorithm...
According to the complexity and coupling of steam turbine-generator, the diagnosis model based on improved genetic algorithm and BP network is proposed in this paper. First, the time factor is considered in the fitness function of genetic algorithm, then use the adaptive crossover rate and mutation rate to improve the genetic algorithm. As soon as the improved genetic algorithm optimizes the initial...
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