Description: 粒子群优化算法(PSO)是一种进化计算技术(evolutionary computation).源于对鸟群捕食的行为研究 PSO同遗传算法类似，是一种基于叠代的优化工具。系统初始化为一组随机解，通过叠代搜寻最优值。但是并没有遗传算法用的交叉(crossover)以及变异(mutation)。而是粒子在解空间追随最优的粒子进行搜索。详细的步骤以后的章节介绍 同遗传算法比较，PSO的优势在于简单容易实现并且没有许多参数需要调整。目前已广泛应用于函数优化，神经网络训练，模糊系统控制以及其他遗传算法的应用领域-Particle Swarm Optimization (PSO) is an evolutionary technology (evolutionary computation). Predatory birds originated from the research PSO with similar genetic algorithm is based on iterative optimization tools. Initialize the system for a group of random solutions, through iterative search for the optimal values. However, there is no genetic algorithm with the cross - (crossover) and the variation (mutation). But particles in the solution space following the optimal particle search. The steps detailed chapter on the future of genetic algorithm, the advantages of PSO is simple and easy to achieve without many parameters need to be adjusted. Now it has been widely used function optimization, neural networks, fuzzy systems control and other genetic algorithm applications Platform: |
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Author:张正 |
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Description: 粒子群优化算法(PSO)是一种进化计算技术(evolutionary computation).源于对鸟群捕食的行为研究 PSO同遗传算法类似，是一种基于叠代的优化工具。系统初始化为一组随机解，通过叠代搜寻最优值。但是并没有遗传算法用的交叉(crossover)以及变异(mutation)。而是粒子在解空间追随最优的粒子进行搜索。详细的步骤以后的章节介绍 同遗传算法比较，PSO的优势在于简单容易实现并且没有许多参数需要调整。目前已广泛应用于函数优化，神经网络训练，模糊系统控制以及其他遗传算法的应用领域-Particle Swarm Optimization (PSO) is an evolutionary technology (evolutionary computation). Predatory birds originated from the research PSO with similar genetic algorithm is based on iterative optimization tools. Initialize the system for a group of random solutions, through iterative search for the optimal values. However, there is no genetic algorithm with the cross- (crossover) and the variation (mutation). But particles in the solution space following the optimal particle search. The steps detailed chapter on the future of genetic algorithm, the advantages of PSO is simple and easy to achieve without many parameters need to be adjusted. Now it has been widely used function optimization, neural networks, fuzzy systems control and other genetic algorithm applications Platform: |
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Author: |
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Description: 先进 PID 控制及其 MATLAB 仿真（教材+相关程序） 刘金琨 著 电 子 工 业 出 版 社
内 容 简 介 本书从 MATLAB 仿真角度系统地介绍了 PID 控制的基本理论、基本方法和应用技术，是作者多年来从事控制系统教学和科研工作的结晶，同时融入了国内外同行近年来所取得的新成果。 全书共分十章，包括连续系统和离散系统的 PID 控制，常用数字 PID 控制，专家 PID和模糊 PID 控制，神经 PID 控制，遗传算法 PID 控制，多变量解耦 PID 控制，几种先进的PID 控制，灰色 PID 控制，伺服系统 PID 控制，PID 实时控制，每种方法都通过 MATLAB 仿真程序进行了说明。本书各部分内容既相互联系又相互独立，读者可根据自己需要选择学习。本书适用于从事生产过程自动化、计算机应用、机械电子和电气自动化领域工作的工程技术人员阅读，也可作为大专院校工业自动化、自动控制、机械电子、自动化仪表、计算机应用等专业的教学参考书。-advanced PID control and MATLAB (materials related procedures) with the electronics industry, Hangzhou Press Description of the book from the perspective of MATLAB simulation system introduced PID control of the basic theory, Basic methods and techniques, is the author of control systems for years to teaching and research work at the crystallization Meanwhile at home and abroad into the peer in recent years has made new achievements. The book is divided into 10 chapters, including discrete and continuous system of PID control system, commonly used digital PID control, Expert PID and fuzzy PID control, neural PID control, genetic algorithm PID control, Multivariable decoupling PID control, several advanced PID control, gray PID control, PID control servo system, PID control in real time, ea Platform: |
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Author:潇耳 |
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Description: 利用遗传算法优化模糊，using ga to optimize the fuzzy control-The use of genetic algorithm to optimize fuzzy, using ga to optimize the fuzzy control Platform: |
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Author:安然 |
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Description: 微粒群算法[PSO ] 是由Kennedy 和Eberhart等于1995 年开发的一种演化计算技术, 来源于对鸟群捕食过程的模拟。PSO同遗传算法类似，是一种基于叠代的优化工具，但与遗传算法使用遗传操作子进行优化不同，利用群体中各个体之间的“协作”与“竞争”关系，根据自身及其竞争者的飞行经验，调整自己的行为。同遗传算法比较，PSO的优势在于简单容易实现并且没有许多参数需要调整。目前已广泛应用于函数优化，神经网络训练，模糊系统控制以及其他遗传算法的应用领域。-Particle Swarm Optimization [PSO] are equal by Kennedy and Eberhart in 1995 developed an evolutionary computing technology, from preying on the birds of the simulation process. PSO with genetic algorithm is similar to an iterative optimization-based tool, but the use of genetic algorithms and genetic manipulation of different sub-optimize the use of groups between the various entities within the " collaboration" and " competitive" relationship, according to themselves and their competition the flying experience, adjust their behavior. Comparison with genetic algorithms, PSO has the advantage of being simple and easy and did not realize the need to adjust the parameters much. Has been widely applied to function optimization, neural network training, fuzzy system control, as well as other genetic algorithm applications. Platform: |
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Author:wzy |
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Description: 排课问题是一个有约束的、多目标的组合优化问题，并且已经被证明是一个NP完全问题。
遗传算法借鉴生物界自然选择和自然遗传机制，使用群体搜索技术，尤其是用于处理传统搜索方法难以解决的复杂的和非线性的问题。经过近40年的发展，遗传算法在理论研究和实际应用中取得了巨大的成功，本文将遗传算法用于排课问题的求解，首先讨论了排课问题中的影响因素、主要约束条件、求解目标和难点，并用数学模型完整地描述了排课问题。其次对多个模糊排课目标进行了定量分析，建立了排课优化目标空间。针对排课问题研究了染色体编码方式以及遗传算子的设计，提出了适应度函数的计算方法。最后对排课问题进行了实验。实验结果表明，其过程的目标值跟踪显示，算法稳健趋优，所得结果令人满意。-Course Scheduling problem is a constrained, multi-objective optimization problem, and has proven to be a NP complete problem.
Genetic algorithms reference biosphere and the natural genetic mechanism of natural selection, using the group search technology, particularly the traditional search methods for handling complex and difficult to solve nonlinear problems. After nearly 40 years of development, the genetic algorithm in the theoretical study and practical application was a great success, this paper genetic algorithm for solving the course timetabling problem, first discussed the impact of factors in the course arrangement, the main constraints, to solve goals and difficulties, and a complete mathematical model to describe the course arrangement. Arranging multiple fuzzy goals followed by a quantitative analysis, the optimal target Arranging space. Arranging for the Study of the chromosome coding and genetic operators design, proposed fitness function is calculated. Finally, the co Platform: |
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Author:张林杰 |
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Description: 遗传算法改进的模糊C均值聚类的matlab源程序,可以运行,格式需要更改-Improved genetic algorithm fuzzy C means clustering matlab source code, you can run, you need to change the format Platform: |
Size: 5120 |
Author:李慧 |
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Description: 人工智能（模糊在自动控制的应用）电动机控制中的简单遗传算法PID参数优化-Artificial intelligence (fuzzy in Automatic Control) motor control in the simple genetic algorithm optimization of PID parameters Platform: |
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Author:卡卡 |
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Description: 这是一个基于改进的免疫遗传的模糊聚类程，敬请大家下载序-This is based on improved immune genetic fuzzy clustering process, please download the sequence we Platform: |
Size: 3072 |
Author:行高 |
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Description: 遗传模糊优化算法，对大量信号的处理算法希望对大家研究有帮助。-Fuzzy genetic optimization algorithm, the algorithm is useful for everyone to want to help. Platform: |
Size: 26624 |
Author:shenyang |
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Description: 一本基于matlab技术的智能控制方面的书籍，包括了神经网络控制，模糊控制，遗传算法控制等。(A book on Intelligent Control Based on MATLAB technology, including neural network control, fuzzy control, genetic algorithm control and so on.) Platform: |
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Author:大漠孤烟客 |
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Description: 高等应用数学问题的MATLAB问题求解，线性、积分方程、代数方程、微分方程、数据插值、函数逼近问题、概率论与数理统计问题的计算机求解，模糊逻辑与模糊推理、遗传算法、小波变换、粗糙集理论等的应用。(Matlab problem solving of higher applied mathematics, computer solving of linear, integral, algebraic, differential, data interpolation, function approximation, probability theory and mathematical statistics, application of fuzzy logic and fuzzy reasoning, genetic algorithm, wavelet transform, rough set theory, etc) Platform: |
Size: 21203968 |
Author:凌澜潇潇 |
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