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   genetic 在 计算机软件及计算机应用 分类中 的翻译结果: 查询用时:0.203秒
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genetic
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    A Study of Network Parallel Computation and Genetic Algorithms in Evaluation of HPM Biological Effects and HPM Antenna Design
    网络并行和遗传算法在HPM生物效应评价和辐射天线设计中的应用研究
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    Shape Conceptual Design based on Intuition Heuristic and Improved Genetic Algorithm
    基于直觉启发和改进遗传算法的形状概念设计
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    Genetic Algorithems Study in Urban Spatial Growth Quantificational Methods
    遗传算法在城市空间增长中的量化方法研究
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    DISCRETE VAR OPTIMIZATION NEAR TO GLOBAL OPTIMUMBY GENETIC ALGORITHM
    基于遗传算法技术的离散无功优化
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    Automatically Generating FuzZy Rules Using Genetic Algorithm
    利用遗传算法自动生成模糊规则
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  “genetic”译为未确定词的双语例句
    A Genetic Algorithm of Small Population Size for Structural Optimization
    一种小群体规模的结构优化GA算法
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    Actual research status and recent applications of genetic algorithms
    关于Genetic算法的研究及应用现状
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    A Genetic Algorithm for Estimations of Parameters under Partial Order Restrictions
    A Genetic Algorithm for Estimations of Parameters under Partial Order Restrictions
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    Application of Genetic Algorithm in Model-Block Construction Organization and Management
    遣传算法在模块化施工组织与管理中的应用
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    A PARTHENO GENETIC ALGORITHM AND ANALYSIS ON ITS GLOBAL CONVERGENCE
    单亲遗传算法及其全局收敛性分析
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  genetic
More particularly, Genetic Algorithms, Artificial Neural Networks and Fuzzy Logic methods seem to be the most promising tools to speed up and optimize the search for new leads and focused libraries.
      
Herein we describe the 3D QSAR study of 4-anilinoquinoline-3-carbonitrile by Genetic Function Approximation (GFA) and Comparative Molecular Field Analysis (CoMFA).
      
In this paper a hybrid algorithm which combines the pattern search method and the genetic algorithm for unconstrained optimization is presented.
      
The algorithm is a deterministic pattern search algorithm, but in the search step of pattern search algorithm, the trial points are produced by a way like the genetic algorithm.
      
Novel Quantum Genetic Algorithm and Its Applications
      
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This paper describes the design thought, systematic constructure and main function of a computer data processing system for plant breeding experiment (PBDPS). This system's functions mainly consist of data Pretreatment, data file management, data statistical analysis and genetic parameter estimating. The results from hundreds of practicai operations show that: This system has many advantages such as novel design thought, complete function, simplicity, and stability, of operation, and high running speed....

This paper describes the design thought, systematic constructure and main function of a computer data processing system for plant breeding experiment (PBDPS). This system's functions mainly consist of data Pretreatment, data file management, data statistical analysis and genetic parameter estimating. The results from hundreds of practicai operations show that: This system has many advantages such as novel design thought, complete function, simplicity, and stability, of operation, and high running speed. It performs satisfactorily both in common use and in practicability. It can be used in managing and statistically analysising data of various experiments.

叙述了植物育种试验数据计算机处理系统(PBDPS)的设计思想、系统结构和主要功能。该系统包含数据预处理、数据文件管理、数据统计分析及遗传参数估算四部分。经过数百次实际运行结果表明,此系统设计思想新颖,功能齐全,操作简便,运行敏捷,实用性和通用性均好,可用于各种试验数据的管理及统计分析。

In this paper,the genetic programming approach is used to discuss the determina-tion of blasting classification of rocks,and the computer intelligence export system is built , whichproved to be feasilble.

运用遗传程序设计方法,对岩体的可爆性等级判别作了初步探讨,提出相应的计算机智能专家系统,结果表明该方法是可行的。

The allocations of reactive sources andthe control of discrete reactive facilities create a largescale non-linear discrete VAR optimization problem,which is a non-convex problem with multiple integerfeasible solutions mathematically. This research attemptsto solve the discrete VAR optimization problem based onsuch a technique that a Genetic Algorithm (GA) isemployed to find out an approximation solution near tothe global optimum. And to speed up the solutionprocedure, an expert system is utilized to provide...

The allocations of reactive sources andthe control of discrete reactive facilities create a largescale non-linear discrete VAR optimization problem,which is a non-convex problem with multiple integerfeasible solutions mathematically. This research attemptsto solve the discrete VAR optimization problem based onsuch a technique that a Genetic Algorithm (GA) isemployed to find out an approximation solution near tothe global optimum. And to speed up the solutionprocedure, an expert system is utilized to provide powersystem information. A real distribution system with 18changeable taps and 7 capacitors is used to demonstratethe validity ofthe approach.

电力系统设备的离散特性使得无功优化问题成为大规模的非线性整数规划问题。用传统的优化算法已无法保证得到全局最优解,为了寻找靠近全局最优解,本文试图应用基于遗传算法(GA)技术求解离散无功优化问题,遗传算法是基于自然选择和自然生物学的随机查寻算法,该算法在随机的条件下试验偶然的新部分,但不是简单的任意查寻,它有希望改进性能并有效地利用系统信息去怀疑新查寻点。为了加速求解,在计算过程中还采用专家系统以提供电力系统的网络信息。计算结果表明了本算法的有效性。

 
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