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A chaos ant lion optimization-based target grouping method

A target and chaotic technology, applied in the field of target grouping based on the chaotic antlion optimization algorithm, can solve problems such as limited global optimization capabilities, unstable grouping results, and manual input of thresholds

Inactive Publication Date: 2019-05-17
AIR FORCE UNIV PLA
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AI Technical Summary

Problems solved by technology

[0004] Although the clustering method is continuously optimized, there are still problems such as the need to pre-specify the number of clusters, manually input the threshold, and fail to meet real-time performance.
[0005] Genetic algorithm is a classic intelligent algorithm, which is widely used in engineering, but it needs to set the number of groups in advance, and due to the limited global optimization ability, there will be problems with unstable grouping results

Method used

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  • A chaos ant lion optimization-based target grouping method
  • A chaos ant lion optimization-based target grouping method
  • A chaos ant lion optimization-based target grouping method

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Embodiment Construction

[0094] The present invention will be described in further detail below in conjunction with the accompanying drawings and embodiments.

[0095] refer to figure 1 , the target grouping method based on self-organizing feature map network of the present invention, specifically comprises the following steps:

[0096] Step 1. Read data

[0097] 1.1) Let the initial time k=1, read the type of the t-th target at time k course Location and speed The value of t is 1, 2, ..., N k , N k is the target head at time k;

[0098] 1.2) In order to facilitate the description of the formation grouping problem, the t-th target sensor data at time k uses a one-dimensional vector said, among them Indicates the tth target attribute at time k, Indicates the t-th target type at time k, Indicates the heading of the t-th target at time k, Indicates the tth target position at time k, Indicates the speed of the t-th target at time k, and the data set of all target sensors at time k i...

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Abstract

The invention provides a chaos ant lion optimization-based target grouping method. The chaos ant lion optimization-based target grouping method specifically comprises the following steps of reading data; cleaning data, using a chaos ant lion optimization algorithm to group the target formation; and outputting the formation grouping result. According to the invention, a Tent chaotic strategy is introduced to initialize a population; the ant lion selection strategy is used for replacing a roulette method to select the ant lion, a new solution is generated for ants and the ant lion with poor fitness in the population through Tent chaotic search, a chaotic operator and random walk of the ants are combined, the performance of the ant lion optimization algorithm is improved, and the accuracy andefficiency of target grouping are improved.

Description

technical field [0001] The invention relates to the field of situation estimation, in particular to a target grouping method based on a chaotic antlion optimization algorithm, which can be used in the fields of situation estimation, intention recognition and the like. Background technique [0002] Due to the large number and types of air targets and the rapidly changing situation, if the target information is not processed and the densely packed target location map is directly provided to decision makers, it may cause information dazzling and make decision makers unable to make accurate judgments. Target grouping can improve information recognition, solve the problem of dazzling information and help decision makers make correct decisions quickly. [0003] At present, typical target grouping methods include clustering methods and genetic algorithms. [0004] Although the clustering method has been continuously optimized, there are still problems such as the need to pre-speci...

Claims

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Application Information

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IPC IPC(8): G06N3/00G06N7/08
Inventor 黄震宇白娟张振兴杨任农王栋
Owner AIR FORCE UNIV PLA
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