Artificial fish-swarm algorithm based on overall information

An artificial fish swarm algorithm and global information technology, applied in the field of artificial fish swarm algorithm, can solve the problems of low algorithm accuracy, high complexity, and slow convergence in the later stage

Inactive Publication Date: 2009-08-26
SHANDONG UNIV
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AI Technical Summary

Problems solved by technology

However, the basic artificial fish swarm algorithm also has shortcomings such as low algorithm accuracy, slow convergence in the later stage, and high complexity.

Method used

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  • Artificial fish-swarm algorithm based on overall information

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Embodiment Construction

[0046] The flow process of the global fish swarm algorithm of the present invention is as shown in the accompanying drawing, comprises the following steps:

[0047] 1. Initialize the settings first, including the number of individuals in the artificial fish school, the initial position of each artificial fish, the field of view of the artificial fish, the maximum number of iterations, the number of attempts, the crowding factor and the threshold for swallowing behavior;

[0048] 2. Calculate the fitness value of each artificial fish, and record the state of the globally optimal artificial fish;

[0049] 3. Evaluate each artificial fish and choose the behavior to be performed;

[0050] 4. Execute the behavior of artificial fish selection, and update the location information of artificial fish;

[0051] 5. Update the state of the global optimal artificial fish;

[0052] 6. If the conditions for the end of the loop are met, output the result, otherwise jump to 2.

[0053] The ...

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Abstract

The invention provides an artificial fish-swarm algorithm based on overall information, comprising the followings steps: (1) firstly initializing settings, (2) calculating the fitness value of each artificial fish and recording the status of overall optimized artificial fish, (3) evaluating each artificial fish and selecting the behaviors to be acted by fish, including feeding, bunching, tailing, biting and jumping, (4) acting the behaviors selected by the artificial fish and updating the position information of the fish based on the overall and local information, (5) updating the status of overall optimized artificial fish, and (6) outputting the result if the condition of loop termination is met, or returning to the step (2). The invention improves the basic artificial fish-swarm algorithm and provides a new fish-swarm optimizing mode and biting and jumping behaviors of the artificial fish, reduces the complexity the algorithm enhances the overall optimizing capability of algorithm and increases the speed and precision of convergence of the algorithm.

Description

technical field [0001] The invention relates to an artificial fish swarm algorithm, specifically adding global optimal information to the update of the artificial fish position, and proposing the swallowing behavior and jumping behavior of the artificial fish, belonging to the technical field of artificial fish swarm algorithm. Background technique [0002] The artificial fish swarm algorithm is a novel and efficient swarm intelligence algorithm. It simulates the behavior of fish swarms for random search. Local information achieves the purpose of global optimization. The basic artificial fish swarm algorithm has a good ability to overcome local extremum and obtain global optimal value. The algorithm is simple and easy to program, and has good convergence performance. However, the basic artificial fish swarm algorithm also has shortcomings such as low algorithm accuracy, slow convergence in the later stage, and high complexity. [0003] Some definitions and basic behavioral ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06N3/00
Inventor 江铭炎程永明袁东风
Owner SHANDONG UNIV
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