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Social learning method facing function optimization

A technology of social learning and function optimization, applied in the field of social learning, can solve problems such as the non-existence of social learning methods for solving function optimization

Inactive Publication Date: 2016-09-28
HENAN POLYTECHNIC UNIV
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Problems solved by technology

At present, there are relatively few research results on social learning methods, and there is no social learning method for solving function optimization problems

Method used

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  • Social learning method facing function optimization

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[0024] In the social learning method oriented to function optimization, the individual represents a solution to the function optimization problem, and the fitness value of the individual represents the intelligence level of the individual, and the fitness value is also used to determine whether the individual is eliminated. operations in the co-evolutionary space. Microspace performs genetic mutation operations, and introduces a greedy operator after the crossover operation and mutation operation, that is, after each operation, the current individual is compared with the newborn individual, and the individual with a better fitness value is retained. In the learning space, the individual performs observation learning and imitation learning in turn; a greedy operator is also introduced in the learning space, that is, after individuals perform imitation learning and observation learning, individuals with better fitness are retained; the belief space is extracted from the learning ...

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Abstract

The present invention proposes a function optimization-oriented social learning method, including selection, crossover, mutation operation, imitation learning operation, observation learning operation, update operation, and influence operation. The evolution process of the operation; the observation learning and imitation learning operations are designed in the learning space; in the observation learning operator, the learning inertia weight and the learning disturbance factor are introduced respectively, taking into account the learning inertia and the learning volatility. , which is helpful to expand the search range of the method and improve the convergence speed of the method; the imitation learning operator introduces a variable search step size to improve the convergence speed of the method. In the belief space, the update function of knowledge and the influence function of culture on microspace are designed. After adopting this method, the solution accuracy can be significantly improved, and the convergence speed is faster.

Description

technical field [0001] The invention relates to a social learning method, in particular to a function optimization-oriented social learning method, belonging to the field of group intelligence methods. Background technique [0002] The swarm intelligence method is based on some laws and cooperative behaviors existing in nature or biological groups, from which people abstract mathematical models and design new methods with powerful problem-solving capabilities. In nature, many organisms work together to complete complex tasks through group cooperation, and the simple behavior of individuals in the group shows intelligent behavior due to the mutual influence between individuals. The research idea of ​​the swarm intelligence method is to study the complex behavior of the biological group and the internal mechanism of the problem-solving ability by modeling and analyzing the simple behavior between individuals, the individual's interaction with the environment and the individual...

Claims

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Application Information

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IPC IPC(8): G06N5/02
CPCG06N5/025
Inventor 刘志中宋成秦靖萱王磊彭维平
Owner HENAN POLYTECHNIC UNIV
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