probability of crossover meaning in English

交叉概率

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Auto - - generating paper is a constrained multi - object optimization problem . this paper presents a way based on genetic algorithm ( ga ) to solve the problem . we define the crossover operator and mutation operator in the real coded and adjust the probabilities of crossover and mutation
系统实现采用三层组织结构,面向学习者、教师、管理员三类用户,具有课程学习、作业、答疑、考试以及交流功能,同时采用java语言来构建智能agent ,解决了个性化学习的问题。
On the vsp with time window , while the restraints of capacity and time windows are changed into object restraints , a mathematic model is established . we use technique such as maximum preserved crossover and selfadaptability change of probability of crossover and mutation , and design genetic algorithm on nature number , which can deal with soft and hard time windows . the excellent solutions are obtained in the application
对于有时间窗的非满载vsp问题，将货运量约束和时间窗约束转化为目标约束，建立了vsp模型，使用最大保留交叉、交叉率和变异率的自适应调整等技术，设计了给予自然数编码的可同时处理软、硬时间窗约束的遗传算法，实验分析取得了较好的结果。
Perfection and adjustment according to system properties , it combines genetic algorithms with fuzzy control , detailed analyzes the problem of designing fuzzy controller and proposes two advanced schemes : first scheme : the change - of - variables are emerged into input variables of the simple fuzzy controllers of oil feeding pump system as one variable , and one pi block is connected after output of fuzzy controllers , consequently the structure of the improved fuzzy controller is analyzed , finally genetic algorithms with adaptive probabilities of crossover and mutation is applied to optimize membership functions and fusing factors of the fuzzy controllers , and the simulation results of before and after optimization are compared
由于在模糊控制器的设计过程中存在较多的人为因素，为了实现根据系统特性对模糊规则和隶属函数进行自动修正、完善和调整，本文将遗传算法和模糊控制结合起来，并针对前面设计的模糊控制器中所存在的问题进行了详细分析，提出了两种改进方案： 1在简单模糊控制器的输入变量中加入了变量变化率的信息，即将输入变量和变量的变化率融合为一个输入量，并在模糊控制器的输出端加入比例、积分环节，然后分析了这种改进后的模糊控制器的解析结构，最后采用改进后的自适应遗传算子的遗传算法对模糊控制器中的隶属函数和融合因子进行优化，并将优化前后的结果作了比较和分析。 2
The study work mainly included the following : ( 1 ) to overcome the premature convergence of the standard genetic algorithm ( sga ) , a genetic algorithm ( ga ) based on fuzzy reasoning was proposed . this method was used to adjust the probabilities of crossover and mutation during the evolution of ga
本文的研究工作主要包括: ( 1 )针对标准遗传算法( sga )的未成熟收敛现象,采用模糊推理运算的方法确定遗传算法中的交叉概率和变异概率,实现交叉概率和变异概率的动态调整,从而改善遗传算法的性能。
Methods to manage each constraint condition were put forward , aiming at the premature and slow convergence of genetic algorithm , this algorithm introduced the combination of genetic algorithm and simulated annealing technology , combining with self - adaptive probabilities of crossover and mutation
提出了对各约束条件处理的方法，针对遗传算法收敛慢等的不足，提出将遗传算法和模拟退后技术相结合，并采用自适应交叉和变异率的解决方法。同时也考虑了混合泵站采用遗传算法求解的具体实现步骤和算法。

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probability of crossover meaning in English

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