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Description: 1。《遗传算法的数学基础》，张文修、梁怡编着 西安交通大学出版社 2000年第一版
遗传算法（genetic algorithm）是模拟自然界生物进化过程与机制求解问题的一类自组织与自适应的人工智能技术，已广泛应用于计算机科学、人工智能、信息技术及工程实践。
本书重点在于阐述遗传算法的数学基础。全书共分3章，第1章给出了遗传算法的几何理论，第2章给出了遗传算法的马尔可夫链分析，第3章给出了遗传算法的收敛理论。
本书可以作为应用数学、计算机科学、系统科学等专业研究生的教材，也可以作为研究遗传算法的参考书。 -1. "Genetic Algorithm mathematical basis," Zhang Xiu, Yi Liang compile Xi'an Jiaotong University Press in 2000 the first edition of the genetic algorithm (genetic algorit hm) is a simulation of natural biological evolution process and mechanisms to solve the problem of a kind of self-organization and adaptive artificial intelligence technology, has been widely used in computer science, artificial intelligence, information technology, and engineering practice. The book focused on the genetic algorithm described math. The book is divided into three chapters, one chapter is a genetic algorithm of the geometric theory Chapter 2 of the genetic algorithm is a Markov chain analysis, presented in Chapter 3 of the genetic algorithm convergence theory. The book can be applied mathemati
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Size: 2689630 |
Author: 孙东 |
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Description: 1。《遗传算法的数学基础》，张文修、梁怡编着 西安交通大学出版社 2000年第一版
遗传算法（genetic algorithm）是模拟自然界生物进化过程与机制求解问题的一类自组织与自适应的人工智能技术，已广泛应用于计算机科学、人工智能、信息技术及工程实践。
本书重点在于阐述遗传算法的数学基础。全书共分3章，第1章给出了遗传算法的几何理论，第2章给出了遗传算法的马尔可夫链分析，第3章给出了遗传算法的收敛理论。
本书可以作为应用数学、计算机科学、系统科学等专业研究生的教材，也可以作为研究遗传算法的参考书。 -1. "Genetic Algorithm mathematical basis," Zhang Xiu, Yi Liang compile Xi'an Jiaotong University Press in 2000 the first edition of the genetic algorithm (genetic algorit hm) is a simulation of natural biological evolution process and mechanisms to solve the problem of a kind of self-organization and adaptive artificial intelligence technology, has been widely used in computer science, artificial intelligence, information technology, and engineering practice. The book focused on the genetic algorithm described math. The book is divided into three chapters, one chapter is a genetic algorithm of the geometric theory Chapter 2 of the genetic algorithm is a Markov chain analysis, presented in Chapter 3 of the genetic algorithm convergence theory. The book can be applied mathemati
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Size: 2689024 |
Author: 孙东 |
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Description: 一个简单的课表排课算法实现，识别课程前后继关系，完成自动排课-a simple Timetable Course Scheduling Algorithm, before subsequent identification courses, complete Automatic Timetable
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Size: 252928 |
Author: anquan |
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Description: 基于MOGA方法的多目标遗传算法程序,本程序为通用包,可自行修改.-MOGA is based on the multi-objective Genetic Algorithms procedures, the procedures for the general packet may amend its own.
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Size: 4096 |
Author: 许峰 |
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Description: 使用遗传算法解决MTSP问题的一种新的染色体设计-The use of genetic algorithms to solve the MTSP problem the design of a new chromosome
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Size: 191488 |
Author: pengchao |
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Description: 一个ＪＡＶＡ原程序，实现遗传算法，算法运行时配有画面，种群的进化情况。-A JAVA original procedure, the realization of genetic algorithm with run-time picture of the evolution of the situation of the population.
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Size: 7504896 |
Author: 杨丹 |
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Description: 这是一个非常简单的遗传算法源代码，是由Denis Cormier (North Carolina State University)开发的，Sita S.Raghavan (University of North Carolina at Charlotte)修正。代码保证尽可能少，实际上也不必查错。对一特定的应用修正此代码，用户只需改变常数的定义并且定义“评价函数”即可。注意代码的设计是求最大值，其中的目标函数只能取正值；且函数值和个体的适应值之间没有区别。该系统使用比率选择、精华模型、单点杂交和均匀变异。如果用Gaussian变异替换均匀变异，可能得到更好的效果。代码没有任何图形，甚至也没有屏幕输出，主要是保证在平台之间的高可移植性。读者可以从ftp.uncc.edu,目录 coe/evol中的文件prog.c中获得。要求输入的文件应该命名为‘gadata.txt’；系统产生的输出文件为‘galog.txt’。输入的文件由几行组成：数目对应于变量数。且每一行提供次序——对应于变量的上下界。如第一行为第一个变量提供上下界，第二行为第二个变量提供上下界，等等。
-This is a very simple genetic algorithm source code, by Denis Cormier (North Carolina State University) developed, Sita S. Raghavan (University of North Carolina at Charlotte) as amended. Code to ensure that as little as possible, in fact, do not have errors. The application of a specific amendment to this code, the user can change the definition of constants and the definition of "evaluation function" can be. Note the code is designed for maximum value, in which the objective function can only take positive and function to adapt to individual values and there was no difference between values. The system uses the ratio of choice, the best model, a single point of hybridization and uniform mutation. If the variation of the replacement of uniform Gaussian mutation may be more effective. Code without any graphics, or even no screen output, mainly to ensure a high portability between platforms. Readers can ftp.uncc.edu, directory coe/evol documents obtained prog.c. Asked to enter the fi
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Size: 4096 |
Author: Kaavield |
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Description: Position Control of DC Motor Using Genetic Algorith Based PID Controller using Genetic algorithm
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Size: 385024 |
Author: renjith |
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Description: This work investigates the practical application of
support vector machine (SVM) to power transformer condition
assessment. Partiuclarly, this paper proposes to integrate the
SVM algorithm with two heuristic optimization algorithms which
are particle swarm optimization algorithm (PSO) and genetic
algorithm optimization (GA). These two optimization algorothms
are used for efficiently and effectively determine the optimal
parameters for SVM. The resulatant two hybrid algorithms, i.e.
SVM-PSO and SVM-GA can improve the performances of the
original SVM algorithm on classifying the incipient faults in
power transformers. Extensive case studies and statistic
comparison among the original SVM, SVM-PSO, and SVM-GA
over multiple datasets are also provided. Calculation results may
demonstrate the effectiveness and applicability of the two hybrid
algorit
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Size: 930816 |
Author: pse |
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