Method of using genetic algorithm to optimize BP neural network system

A BP neural network and genetic algorithm technology, applied in neural learning methods, biological neural network models, etc., can solve the problems of insufficient local search ability and long time

Inactive Publication Date: 2017-03-15
SHANGHAI DIANJI UNIV
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Problems solved by technology

However, its local search ability is not enough, and some studies have shown that the genetic algorithm can reach a...

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  • Method of using genetic algorithm to optimize BP neural network system
  • Method of using genetic algorithm to optimize BP neural network system
  • Method of using genetic algorithm to optimize BP neural network system

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[0060] Below in conjunction with specific embodiment, further illustrate the present invention. It should be understood that these examples are only used to illustrate the present invention and are not intended to limit the scope of the present invention. In addition, it should be understood that after reading the teachings of the present invention, those skilled in the art can make various changes or modifications to the present invention, and these equivalent forms also fall within the scope defined by the appended claims of the present application.

[0061] BP neural network, also known as backpropagation neural network, is a network with 3 or more layers without feedback and no interconnection within the layer. Its structure is as follows: figure 1 shown. In addition to the input layer and output layer, the BP neural network also includes one or more hidden layers. The neurons in each layer are fully connected, and there is no connection between neurons in the same layer....

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Abstract

The invention provides a method of using genetic algorithm to optimize a BP neural network system. The genetic algorithm is used to optimize the weight and the threshold of the neural network, and optimized searching space is located in solution space. The searching space is used as the initial weight and the initial threshold of the searching of the neural network, and the local searching capability of the neural network is used to search an optimal solution in the searching space. The method provided by the invention is used to combine the advantages and the disadvantages of the BP neural network and the genetic algorithm, and then the convergence speed of the network is accelerated, and therefore precision of a model is effectively improved, and the optimized combination of the two research directions, namely the BP neural network and the genetic algorithm, is realized. A system is widely used for an intelligent detection field, a non-linear prediction field, a pattern recognition field, a robot control field, and other fields, and has good practicability.

Description

technical field [0001] The invention relates to a model system for optimizing a BP (Back Propagation) neural network by using a genetic algorithm, and belongs to the technical field of artificial intelligence. Background technique [0002] Artificial neural network is an intelligent information processing system based on imitating the structure and function of the human brain system and reflecting some characteristics of the human brain. At present, artificial neural networks have been widely used in many fields. These application fields mainly include intelligent detection, nonlinear prediction, pattern recognition, robot control, etc. With the further development of artificial neural network and more in-depth research, the application prospect of artificial neural network will be broader. [0003] Genetic algorithm (Genetic algorithm, GA) is an adaptive global optimization probability search algorithm formed by simulating the genetic and evolution process of organisms in...

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Application Information

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IPC IPC(8): G06N3/08
CPCG06N3/084G06N3/086
Inventor 熊玉梅
Owner SHANGHAI DIANJI UNIV
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