针对蚂蚁算法的不足，该文提出了一种自适应蚁群算法。
In order to overcome the shortcoming of basic ant algorithm, a new ant algorithm, Adaptive ant Colony algorithm (AACA), is proposed in this paper.
针对多极值连续函数优化问题，提出了一种自适应蚁群算法。
An adaptive ant colony algorithm is presented for the optimization of multi-minimum continuous function.
基于分布式数据挖掘技术，提出了一种基于自适应蚁群算法的分布式分类规则算法。
A distributed classification rule mining based on ant colony algorithm is proposed, which is based on distributed database structure.
本文根据影响并行蚁群算法性能的关键因素，提出了一种自适应的并行蚁群算法。
An adaptive parallel ant colony algorithm is presented by considering the critical factors influencing the parallelization of the ant colony algorithm.
最后，针对模型的具体特点，设计模型解的编码方式，并采用基于云模型的参数自适应蚁群遗传算法进行仿真，结果表明了模型和算法的有效性。
At last, an effective algorithm model taking advance of a skillful encoding method is designed and called ACGA with self-adaptation adjustment of parameters based on cloud models.
最后，针对模型的具体特点，设计模型解的编码方式，并采用基于云模型的参数自适应蚁群遗传算法进行仿真，结果表明了模型和算法的有效性。
At last, an effective algorithm model taking advance of a skillful encoding method is designed and called ACGA with self-adaptation adjustment of parameters based on cloud models.
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