Grey wolf optimization method based on dimension learning strategy and Levy flight

A technique for optimizing methods and dimensions

Pending Publication Date: 2021-11-26
JILIN UNIV
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Problems solved by technology

[0004] The purpose of the present invention is to use the strategy of dimensional learning among the three leader wolves to construct model wolves, combined with Levi's flight to solve the problem of weakened global exploration ability and premature convergence problems caused by wolves all learning from model wolves and the dimensional learning strategy and Gray Wolf Optimization Method for Levi's Flight

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  • Grey wolf optimization method based on dimension learning strategy and Levy flight
  • Grey wolf optimization method based on dimension learning strategy and Levy flight
  • Grey wolf optimization method based on dimension learning strategy and Levy flight

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Embodiment Construction

[0042]The present invention is aimed at the problem that the Alpha, Beta and Delta information of the three leader wolves may conflict or contradict each other in the standard gray wolf algorithm, and uses the strategy of dimension learning to construct a model wolf among the three leader wolves to protect the potentially useful position of the prey. Information, so as to more effectively guide the position update of the wolves, and then combined with Levi’s flight to solve the problem of weakened global exploration ability and possible premature convergence caused by the wolves learning from model wolves, and finally designed a dimension-based learning Strategies and algorithms for gray wolf optimization of Levy's flight.

[0043] The present invention will be described in further detail below in conjunction with accompanying drawing:

[0044] Step 1: Build a model wolf using a dimensionality learning strategy in the leadership of the gray wolf optimization algorithm:

[004...

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Abstract

The invention discloses a grey wolf optimization method based on a dimension learning strategy and Levy flight, and belongs to the technical field of system identification. The grey wolf optimization method based on the dimension learning strategy and the Levey flight aims to construct a model wolf by using the dimension learning strategy in three leading wolves, and solves the problems that global exploration ability is weakened and early maturity convergence is possibly generated due to the fact that a wolf group learns to the model wolf by combining the Levey flight. The method comprises the following steps: constructing a model wolf in a leader layer of a grey wolf optimization method by using a dimension learning strategy; applying the model wolf in the step 1 to wolf pack updating, and a grey wolf optimization method based on a dimension learning strategy is designed in combination with Levy flight. The performance of the standard grey wolf optimization algorithm is greatly improved, and the convergence speed and the convergence precision of the grey wolf optimization algorithm are improved.

Description

technical field [0001] The invention belongs to the technical field of system identification. Background technique [0002] In the real world, there are many optimization problems to be solved, and optimization techniques are developed rapidly because of this. These techniques in most cases require finding the derivative of the objective function of the problem in question. But for some reason, the derivative of the function is sometimes very difficult to find, and sometimes it is impossible to find it at all. As an important non-derivative algorithm, swarm intelligence optimization algorithm has attracted more and more attention because of its strong search ability, simple implementation, few parameters, and strong ability. [0003] The gray wolf optimization algorithm is a well-performing swarm intelligence optimization algorithm, and its search mechanism is established by imitating the strict leadership hierarchy and group behavior during hunting in gray wolf groups. T...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06N3/00
CPCG06N3/006
Inventor 周淼磊刘鑫洋王一帆
Owner JILIN UNIV
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