基本遗传算法,basic genetic algorithm
1)basic genetic algorithm基本遗传算法
1.In order to improve basic genetic algorithm’s premature convergence and random roam and verify improved algorithm’s application effect in civil engineering,the article brings forward four improved measures,with which adaptive and improved genetic algorithm came into being.为了改进基本遗传算法的早熟收敛、随机漫游,验证改进后的算法在土木工程中的应用效果,提出4点改进措施,形成自适应遗传算法。
2.Based on basic genetic algorithm theory and its practice course that this paper uses,some improved measures to its shortcomings are presented: by means of the chaos serial s properties of "ergodicity,randomness,regularity",original population is generated;the strategy that the best individual is saved and the worst individual is replaced .基于对本文所采用的基本遗传算法的原理和实施过程介绍的基础上,针对其缺陷提出改进措施:利用混沌序列的“遍历性、随机性、规律性”的特点生成初始种群;采用最优个体储存、最差个体替换策略。
3.In view of poor convergence and partially converge of basic genetic algorithm(BGA),an new improved algorithm,two-stage genetic algorithm is proposed.针对基本遗传算法(简称BGA)常常存在局部收敛以及收敛解精度不高等方面的不足,提出了一种改进的算法——两阶段遗传算法,给出了算法的结构及具体的实施策略,进而利用Mark-ov链理论和仿真技术分析了该算法的收敛性能,结果表明该算法具有操作简单、鲁棒性强等特点,不仅可以有效地避免寻优过程中的“早熟”现象,而且在很大程度上能提高最优解精度,适合于大规模、高精度的优化问题。
英文短句/例句

1.Solving the 0-1 s knapsack Problem by Genetic Algorithm;用基本遗传算法解决0-1背包问题
2.An Automatic Extraction Study of Chinese Basic Vocabulary Based on Genetic Algorithms;基于遗传算法的汉语基本词汇自动提取研究
3.Clustering and Classification of Data and Text Using Such Technologies as Genetic Algorithm基于遗传算法等技术的数据与文本聚分类研究
4.Research of Text Classification and Clustering Based on Hybrid Parallel Genetic Algorithm;基于混合并行遗传算法的文本分类及聚类研究
5.Research on Chinese Text Keywords Extraction Based on Genetic Algorithm;基于遗传算法的汉语文本主题词提取研究
6.Construction time-cost-quality trade-off based on genetic algorithms;基于遗传算法的项目工期成本质量综合优化
7.The Research of Quantity cost Optimization and Control Based on Genetic Algorithm;基于遗传算法的质量成本优化及控制研究
8.Research on Text Categorization Based on Genetic Algorithm and Fuzzy Clustering基于遗传算法与模糊聚类的文本分类研究
9.Feature Selection for Chinese Text Clustering Based on HowNet and Genetic Algorithm基于《知网》和遗传算法的中文文本聚类特征选择
10.Combination of Rough Sets and Genetic Algorithms for Text Classification基于粗糙集和遗传算法的文本分类研究
11.Text Watermarking Algorithm Based on the Tone of Chinese Characters and Genetic Algorithm一种基于遗传优化和汉字声调的文本水印算法
12.Cost Optimization of Highway Construction Project Based on Genetic Algorithm基于遗传算法的公路施工项目成本优化研究
13.MPPT Algorithm Based on Genetic Algorithm with Perturbation and Observation Control基于遗传算法和扰动观察法的MPPT算法
14.Optimization Combination Genetic Algorithm Based on Matrix Genetic Operator一种基于矩阵遗传算子的优化组合遗传算法
15.Research on QoS Multicast Routing Algorithm Based on Genetic Algorithm;基于遗传算法的QoS组播路由算法研究
16.QoS Multicast Routing Based on Immune Genetic Algorithm;基于免疫遗传算法的QoS组播路由算法
17.QoS Routing Algorithm Based on Genetic Algorithm Optimization Study;基于遗传算法优化QoS路由算法的研究
18.Multiple Sequence Alignment Using Genetic Algorithm;基于遗传算法的多序列比对算法研究
相关短句/例句

Simple Genetic Algorithm基本遗传算法
1.Realization of Simple Genetic Algorithm Based on Matlab;利用MATLAB编程实现了基本遗传算法(SGA),并构作了SGA工具库函数,通过仿真示例验证了该实现方法的有效性,表明它能够对函数进行全局寻优。
3)SGA基本遗传算法
1.Surface Ship Target Recognition Research Based on SGA;应用基本遗传算法进行水面舰船目标识别研究
4)simple genetic algorithm(SGA)基本遗传算法(SCA)
5)Genetic Algorithms基因遗传算法
1.Optimization of Preparation of Monodisperse Fluorescent Microsphere——Using Genetic Algorithms;应用基因遗传算法优化单分散荧光微球制备工艺
2.Genetic Algorithms and Their Applications to Aerodynamic Optimization Problems;基因遗传算法及气动外形最优化设计
3.This paper presents an approach based on the genetic algorithms to estimate the system parameters and time delays in the feedback simultaneously through the minimization of residual error of system equation.以方程残差作为目标函数 ,运用基因遗传算法同时辨识受控系统的反馈时滞和物理参数。
6)genetic algorithm遗传基因算法
1.Improvement of genetic algorithm in verification;遗传基因算法在验证中的改进
2.In this paper, the genetic algorithm in the continuous domain is presented.介绍了一种全新的优化算法——连续域中的遗传基因算法(GA),提出了基于GA的加工过程切削用量优化计算方法,给出了铣削用量优化算例。
3.An optimal design configuration of leading edge extensions(LEXs) is presented based on the standard genetic algorithms(GAs).用遗传基因算法优化设计了翼-身-尾全机模型机翼边条。
延伸阅读

数值遗传算法分子式:CAS号:性质:基于自然界生物进化机制的一种全局最优化方法。在遗传算法中,被研究体系的响应曲面看作为一个群体,响应曲面上的每一个点作为群体中的一个个体,个体用多维向量或矩阵来描述,组成矩阵的和向量的参数(元素)相应于生物中组成染色体的基因。染色体用固定长度的二进制位串(bit string)表示。通过交换(染色体基因交换)、突变(改变染色体基因)等遗传操作,在参数的一定范围内进行随机搜索,不断改善数据结构,构造出不同的向量,相当于得到了被研究问题的不同的解(一个个体相当于一个解)。目标函数较优的点被保留,较差的点被淘汰,最后达到全局最优化。