RBF neural network optimization method based on improved whale algorithm

A neural network and optimization method technology, applied in the field of neural network optimization, can solve the problems of lack of flexibility of whale algorithm, easy to fall into local optimum, ignoring global information, etc., to achieve precise suppression of chaotic characteristics, great flexibility and directionality, The effect of increasing the speed of convergence

Pending Publication Date: 2021-01-15
JIANGSU UNIV OF SCI & TECH
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Problems solved by technology

[0006] The purpose of the present invention is to solve the technical problems that the existing whale algorithm lacks flexibility, ignores global information when updating, converges slowly, and is easy to fall into local optimum. On this basis, a RBF neural network optimization based on the improved whale algorithm is proposed method

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  • RBF neural network optimization method based on improved whale algorithm
  • RBF neural network optimization method based on improved whale algorithm
  • RBF neural network optimization method based on improved whale algorithm

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[0046]Hereinafter, exemplary embodiments of the present invention will be described with reference to the accompanying drawings. It should be understood that the drawings shown and the specific implementations described are only exemplary, and are intended to illustrate the application principle of the present invention, and do not limit the application scope of the present invention.

[0047]The invention discloses an RBF neural network optimization method based on an improved whale algorithm.figure 2 The topological structure of RBF neural network is given, and the sea clutter prediction model of RBF neural network is taken as an example.figure 1 The specific implementation steps of this example are given:

[0048]Step 1: Determine the topology of the RBF neural network, and encode the initialization parameters of the network into the position vector of the individual whale. The initialization parameters include the data center of the network, the data width and the network weight. The ...

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Abstract

The invention belongs to the technical field of neural network optimization, and particularly relates to an RBF neural network optimization method based on an improved whale algorithm, and the methodcomprises the steps: using improved whale algorithm for searching an optimal initial parameter of an RBF neural network, building a sea clutter prediction model through a training network, and carrying out prediction and inhibition of sea clutters of an adjacent unit; dynamically calculating the fitness mean value of each generation of population in the whale algorithm iteration process, setting the fitness threshold of the next generation of population, dividing the whole population into a high-quality whale sub-population and a non-high-quality whale sub-population, and enabling the high-quality whale sub-population and the non-high-quality whale sub-population to be close to the global optimum at different step lengths; besides, when contraction updating is executed, the idea of substance exchange is introduced so that newly generated particles can be globally recognized and can be stably searched for in the globally optimal direction, the improved whale algorithm has global and local search capacity in the iteration process, and the convergence speed and precision are improved.

Description

technical field [0001] The invention belongs to the technical field of neural network optimization, in particular to an RBF neural network optimization method based on an improved whale algorithm. Background technique [0002] High-frequency radar emits high-frequency electromagnetic waves, and short waves can diffract and propagate along the ocean surface, realizing all-weather and beyond-horizon monitoring of the ocean. At present, high-frequency radar has been widely used in many fields such as maritime early warning, maritime resource detection, and maritime rescue. The innovative research on the high-frequency radar system of RANGER, an EU maritime traffic monitoring project, has enabled high-frequency radar to be applied better and better in more and more fields. However, when high-frequency radar detects sea targets, the echoes are often mixed with a large number of interference echoes, and the main interference component is sea clutter, which appears relatively larg...

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Application Information

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IPC IPC(8): G06N3/04G06N3/00
CPCG06N3/006G06N3/045
Inventor 尚尚何康宁王召斌杨童刘明
Owner JIANGSU UNIV OF SCI & TECH
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