蚁群优化器作为自适应分类器

2012 International Conference on Communication, Information & Computing Technology (ICCICT) Pub Date : 2012-12-31 DOI:10.1109/ICCICT.2012.6398106

A. Tayade, L. Ragha

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引用次数: 4

摘要

优化算法之所以在优化、模式识别、特征提取、特征选择等诸多领域得到广泛应用，主要是因为它能够解决路径规划中的优化问题。在众多的优化算法中，蚁群优化算法是最流行的一种优化算法。近年来，许多动态构造蚁群优化解的算法得到了发展。几种蚁群优化算法在组合优化问题上表现出良好的性能。其中，与蚂蚁系统和蚁群系统相比，最大最小蚂蚁系统在解决旅行商问题上的表现相对较好。提出了一种利用蚁群优化器作为自适应分类器的分类方法。采用蚁群算法的分类器可以在自适应环境下提供更高效的分类方法。

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Ant Colony Optimizer as an Adaptive Classifier

The widespread popularity of Optimization Algorithm in many fields such as Optimization, Pattern Recognition, Feature Extraction, Feature Selection etc. is mainly due to their ability to solve optimization problems in path planning. Out of many kinds of optimization algorithms, Ant Colony Optimization Algorithm is one of the most popular optimization algorithms. Many algorithms that dynamically construct solution to Ant Colony Optimization have increased in recent years. Several ant colony optimization algorithms present a promising performance on combinatorial optimization problem. Among them, Max Min Ant System performs comparatively better for Travelling Salesman Problem as compared to Ant System and Ant Colony System. A method is proposed for Classification using Ant Colony Optimizer as an Adaptive Classifier. The Classifier using ACO may give more efficient and effective method for classification in the adaptive environment.

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来源期刊

2012 International Conference on Communication, Information & Computing Technology (ICCICT)

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