It is a new hot subject rised in recent years to solve TSP with intelligent optimization algorithms.
基于智能优化算法求解tsp问题，是近年来刚刚兴起的热门课题。
Method of. modeling using the intelligent optimization algorithms is discussed for AC variable frequency speed regulation system.
针对交流变频调速系统，探讨了应用智能优化算法实验建模方法。
Colony evolution based intelligent optimization algorithms have deficiencies of poor computational efficiency and are prone to premature during the solution process.
基于群体进化的智能优化算法在求解过程中存在计算效率低和易于早熟收敛等缺点。
To solve the above problems, this paper adopts intelligent optimization algorithms to search for the optimal threshold, aiming to maximize the efficiency and accuracy.
为了解决以上问题，本文采用智能优化算法来搜寻最优阈值，旨在最大限度地提高寻优效率和寻优精度。
Optimization methods, the theory and algorithm of solving optimization problems, can be divided into two parts, the traditional optimization algorithms and intelligent optimization algorithms.
最优化方法是解决最优化问题的理论和算法，主要包括传统优化算法和智能优化算法两大类。
Novel intelligent algorithms based on bionics become more and more popular for solving dynamic optimization problems in recent years.
新型的智能仿生算法在动态优化问题中的应用也逐渐增多。
The paper discussed the modern artificial intelligent algorithms of reactive power optimization, summarized and analyzed the characteristics and usage situation of genetic algorithms.
探讨了求解无功优化的现代人工智能算法，总结分析了遗传算法的特点及使用情况。
On the basis of comparison of intelligent control technologies, their major schemes, features and optimization algorithms are expounded in detail with examples.
在智能控制技术比较的基础上，较详细地阐述了智能控制技术主要方式的特点及优化算法，并举例说明。
However, comparing with other intelligent algorithms, immune algorithm also owns some disadvantage, like premature convergence and poor ability in local optimization.
然而，类似于其它新型智能算法，人工免疫算法也存在一些不足，如存在早熟收敛、局部搜索能力不足等。
The parameters of the PID controllers, however, are very much dependent on the accuracy of the models. This paper studies the control algorithms for aeroengines based on intelligent optimization.
本文重点研究如何利用先进的智能优化算法改进传统的发动机控制系统，并进一步对前沿的智能控制算法及其研究方向进行探索性研究。
The parameters of the PID controllers, however, are very much dependent on the accuracy of the models. This paper studies the control algorithms for aeroengines based on intelligent optimization.
本文重点研究如何利用先进的智能优化算法改进传统的发动机控制系统，并进一步对前沿的智能控制算法及其研究方向进行探索性研究。
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