Description: 粒子群优化算法！！！
系统地介绍了粒子群优化算法,归纳了其发展过程中的各种改进如惯性权重!收敛因子!跟踪并
优化动态目标等模型\"阐述了算法在目标函数优化!神经网络训练!模糊控制系统等基本领域的应用并
给出其在工程领域的应用进展,最后,对粒子群优化算法的研究和应用进行了总结和展望,指出其在计算
机辅助工艺规划领域的应用前景\"-PSO algorithm! ! ! A systematic introduction to PSO algorithm, summed up its development process such as the improvement of inertia weight! Convergence factor! track and dynamic optimization model objectives, "explained the algorithm optimization objective function! Neural Network Training! Fuzzy Control System basic areas of application and gives the project from its the application domain, finally, the PSO algorithm research and application of the summary and outlook. pointed out in the field of computer-aided process planning applications prospects " Platform: |
Size: 53571 |
Author:八云 |
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Description: 多阶段决策过程（ multistep decision process ）是指 这样一类特殊的活动过程，过程可以按时间顺序分解成若干个相互联系的阶段，在每一个阶段都需要做出决策，全部过程的决策是一个决策序列。 动态规划 （ dynamic programming ）算法 是解决 多阶段决策过程最优化问题 的一种常用方法，难度比较大，技巧性也很强。利用动态规划算法，可以优雅而高效地解决很多贪婪算法或分治算法不能解决的问题。动态规划算法的基本思想是：将待求解的问题分解成若干个相互联系的子问题，先求解子问题，然后从这些子问题的解得到原问题的解； 对于重复出现的子问题，只在第一次遇到的时候对它进行求解，并把答案保存起来，让以后再次遇到时直接引用答案，不必重新求解 。动态规划算法将问题的解决方案视为一系列决策的结果，与贪婪算法不同的是，在贪婪算法中，每采用一次贪婪准则，便做出一个不可撤回的决策；而在动态规划算法中，还要考察每个最优决策序列中是否包含一个最优决策子序列，即问题是否具有最优子结构性质。
-multi-stage decision-making process (multistep decision process) is that like a special kind of process, the process can be time-sequence decomposed into a number of interrelated stage, in every stage of a need to make a decision, all of the decision-making process is a sequence of decision-making. Dynamic Programming (dynamic programming) algorithm is a multi-stage decision-making process optimization asked that's a common method was more difficult, skills also have a strong character. Using dynamic programming algorithm can be elegant and efficient solution for many greedy algorithm or partition algorithm to solve the problem. Dynamic programming algorithm is the basic idea : to be solving the problem is decomposed into a number of interrelated issues son, Solving the problem first s Platform: |
Size: 3072 |
Author:汤烈 |
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Description: 一种新的随机优化技术:基于群落动态分配的粒子群优化算法(Community Dynamic Assignation-based Particle Swarm Optimization,CDAPSO)。新算法通过动态改变粒子群体的组织结构和分配特征来维持寻优过程中启发信息的多样性,从而使其全局收搜索能力得到了显著提高,并且能够有效避免早熟收敛问题。-a new stochastic optimization techniques : Community-based dynamic allocation of PSO algorithm (Dynamic Community Assigna tion-based Particle Swarm Optimization, CDAPSO). New Algorithm for dynamic change particle group's organizational structure and distribution to maintain the optimization process enlightening information diversity, thus the overall admission search capability has been significantly improved, and can effectively prevent premature convergence. Platform: |
Size: 6144 |
Author:wuyuqian |
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Description: 多目标优化进化算法目前公认效果收敛性最好的算法NSGA2c++源码,具有一般性，可在此基础上继续改进，对实现其他多目标优化算法很有帮助.-Multi-objective optimization evolutionary algorithm is currently the best recognized effect of convergence of the algorithm NSGA2c++ Source, with the general, could be on this basis to continue to improve the achievement of other multi-objective optimization algorithm helpful. Platform: |
Size: 116736 |
Author:antercy |
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Description: 《实用最优化方法 （第三版）》 该教材介绍了线性规划、非线性规划、多目标规划、整数规划和动态规划的基本理论、计算方法及其应用。书中着重阐述了最优化的基本原理和在实际应用中比较有效的计算方法及其在计算机上的实现等内容。- Practical Optimization Methods (third edition) The materials introduced linear programming, nonlinear programming, multi-objective programming, integer programming and dynamic programming of the basic theory, calculation methods and their applications. The book focuses on the optimization of the most basic principle and in practical applications more effective method of calculation and its realization on the computer and so on. Platform: |
Size: 12047360 |
Author:nc21lym |
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Description: These are matlab and simulink files to model the membrane crystallization system, including the matlab file to get the optimation point of this system, and 3 simulink files, which are static model and 2 dynamic models. There has PID control and feed forward control for the dynamic models. Platform: |
Size: 47104 |
Author:eddyye |
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Description: 使用动态规划求多段图的C++源程序，用于满足最优化问题且问题能转换成一个有向图问题的求解，可以直接运行！-The use of dynamic programming for multi-stage plan of C++ source code, designed to meet the optimization problem and the problem can be converted into a directed graph to solve the problem, you can directly run! Platform: |
Size: 229376 |
Author:张凯兵 |
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Description: 细菌觅食随机优化论文及matlab源码。该算法属于进化算法的一种，可以处理全局优化、多目标优化、约束优化和动态优化等问题。-Bacterial feeding stochastic optimization papers and matlab source code. The algorithm belongs to a kind of evolutionary algorithm that can deal with global optimization, multi-objective optimization, constrained optimization and dynamic optimization problems. Platform: |
Size: 2452480 |
Author:bxingliu |
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Description: 最新SD期刊上关于改进型PSO算法，我是通过学校内部数据库在SD下载的哦！包括《A dynamic inertia weight particle swarm optimization algorithm》、《Adaptive Particle Swarm Optimization》、《Cyber Swarm Algorithms – Improving particle swarm optimization using adaptive memory strategies》。这三篇都是比较有研究价值的学术文章，识货的请下载！-Particle swarm optimization (PSO) algorithm has been developing rapidly and has been applied widely since it was introduced, as it is easily understood and realized. This paper presents an improved particle swarm optimization algo-rithm (IPSO) to improve the performance of standard PSO, which uses the dynamic inertia weight that decreases according to iterative generation increasing. It is tested with a set of 6 benchmark functions with 30, 50 and 150 diff erent
dimensions and compared with standard PSO. Experimental results indicate that the IPSO improves the search perfor-mance on the benchmark functions signifi cantly. Platform: |
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Author:asdwe |
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Description: Genetic algorithms (GAs) have recently been accepted as powerful approaches to
solving optimization problems. It is also well-accepted that building block construction
(schemata formation and conservation) has a positive influence on GA behavior.
Schemata are usually indirectly evaluated through a derived structure. We introduce
a new approach called the Constructive Genetic Algorithm (CGA), which allows
for schemata evaluation and the provision of other new features to the GA. Problems
are modeled as bi-objective optimization problems that consider the evaluation of two
fitness functions. This double fitness process, called fg-fitness, evaluates schemata and
structures in a common basis. Evolution is conducted considering an adaptive rejection
threshold that contemplates both objectives and attributes a rank to each individual in
population. The population is dynamic in size Platform: |
Size: 107520 |
Author:asad |
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Description: 用基本遗传算法求解一维无约束优化问题
用顺序选择遗传算法求解一维无约束优化问题
用动态线性标定适应值的遗传算法求解一维无约束优化问题
用大变异遗传算法求解一维无约束优化问题
用自适应遗传算法求解一维无约束优化问题
用双切点遗传优化求解一维无约束优化问题
用多变异位自适应遗传优化求解一维无约束优化问题
-The basic genetic algorithm with one-dimensional sequence of unconstrained optimization problems using genetic algorithm selected one-dimensional non-linear constrained optimization problem of dynamic calibration of genetic algorithm to adapt to the value of one-dimensional unconstrained optimization genetic algorithm with a large variation of one-dimensional unconstrained adaptive genetic algorithm for optimization problem solving unconstrained optimization problems one-dimensional cut by two-dimensional point of GA for solving a problem of unconstrained optimization adaptive genetic optimization with variable ectopic solving one-dimensional unconstrained optimization problem Platform: |
Size: 6144 |
Author:胖子 |
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Description: 本书包括无约束优化计算，约束优化计算，动态优化计算三部分。书中详细介绍了他们的算法原理和计算步骤。-This book includes unconstrained optimization, constrained optimization, dynamic optimization of three parts. The book details the principles of their algorithm and calculation steps. Platform: |
Size: 3258368 |
Author:jiang |
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Description: 采用改进动态寻优方法，并结合单点、改进的交叉算子与轮盘赌、两两竞争遗传算子分别求解函数最小值，仿真结果表明其差异与优劣。-Improved dynamic optimization method, combined with a single point, improved crossover and roulette, pairwise genetic operators were competing to solve the minimum function, simulation results show that the differences and advantages and disadvantages. Platform: |
Size: 13312 |
Author:李瑜锋 |
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Description: 动态算法的讲解，经典例题和相应的源代码，是学习动态规划的好材料(dynamic programming (also known as dynamic optimization) is a method for solving a complex problem by breaking it down into a collection of simpler subproblems, solving each of those subproblems just once, and storing their solutions) Platform: |
Size: 61440 |
Author:扎西得勒阿斌 |
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Search - dynamic optimization