一种基于T2FPSO的type-2模糊支持向量机场景分类方法

doi:10.16182/j.issn1004731x.joss.201612007

系统仿真学报 ›› 2016, Vol. 28 ›› Issue (12): 2925-2933.doi: 10.16182/j.issn1004731x.joss.201612007

一种基于T2FPSO的type-2模糊支持向量机场景分类方法

徐淑琼, 袁从贵

东莞职业技术学院,广东东莞 523808

收稿日期:2016-02-26 修回日期:2016-05-24 出版日期:2016-12-08 发布日期:2020-08-13
作者简介:Xu Shuqiong(1981-), Female, Guangdong, China, Doctor, Lecturer, Research interests include intelligent control systems and signal processing.
基金资助:
The projects of Guangdong Natural Science Foundation (2014A030310380, 2015A030310257) , The project of Dongguan Polytechnic Foundation (2015a05)

Effective T2FPSO-Based T2FSVM Scene Classification Algorithm

Xu Shuqiong, Yuan Conggui

Dongguan Polytechnic, Dongguan 523808, China

Received:2016-02-26 Revised:2016-05-24 Online:2016-12-08 Published:2020-08-13
About author:Xu Shuqiong(1981-), Female, Guangdong, China, Doctor, Lecturer, Research interests include intelligent control systems and signal processing.
Supported by:
The projects of Guangdong Natural Science Foundation (2014A030310380, 2015A030310257) , The project of Dongguan Polytechnic Foundation (2015a05)

摘要/Abstract

摘要： 为提高机器视觉识别的选择性和鲁棒性,给出了基于T2FPSO优化的T2FSVM场景分类方法。算法中,设计了type-2模糊支持向量机模型以提高其泛化能力并得到正确的场景分类信息;为提高PSO在不确定环境中的优化能力,构建了融合type-2模糊集概念的T2FPSO优化算法,并采用区间type-2模糊逻辑系统推理得到其惯性权值。实验结果表明所提出的场景分类方法可对不确定信息进行有效处理。

关键词: 场景分类, type-2模糊粒子群优化, type-2模糊支持向量机, type-2模糊逻辑系统

Abstract: A systematic design methodology of Type-2 Fuzzy Particle Swarm Optimization (T2FPSO) based Type-2 Fuzzy Support Vector Machine (T2FSVM) classification system was proposed for scene image to improve selectivity and robustness in the machine vision. In the novel classification system, the T2FSVM model was presented to realize a comprehensive learning of the correct class and show the superiority of the generalization capability for classification problem. Furthermore, in order to improve the performance of PSO on complex uncertain environments, the type-2 fuzzy concept was incorporated to PSO to construct T2FPSO searching algorithm, in which the interval type-2 fuzzy inertia weight was designed using an Interval Type-2 Fuzzy Logic System (IT2FLS). Experimental studies indicate that the T2FPSO-T2FSVM approach is effective to deal with uncertainties for scene classification, when scene images are corrupted by the hybrid noises or captured by different view angels and light conditions.

Key words: scene classification, type-2 fuzzy particle swarm optimization (T2FPSO), type-2 fuzzy support vector machine (T2FSVM), type-2 fuzzy logic system (T2FLS)

中图分类号:

TP391.9

徐淑琼, 袁从贵. 一种基于T2FPSO的type-2模糊支持向量机场景分类方法[J]. 系统仿真学报, 2016, 28(12): 2925-2933.

Xu Shuqiong, Yuan Conggui. Effective T2FPSO-Based T2FSVM Scene Classification Algorithm[J]. Journal of System Simulation, 2016, 28(12): 2925-2933.

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一种基于T2FPSO的type-2模糊支持向量机场景分类方法

Effective T2FPSO-Based T2FSVM Scene Classification Algorithm

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