Description: pso算法的代码，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，-PSO algorithm code is based on an iterative optimization tools. Initialize the system for a group of random solutions, through iterative search for the optimal values, Platform: |
Size: 128274 |
Author:张林 |
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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: 6744 |
Author:wuyuqian |
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Description: 主要功能： 1.可以搜索局域网内的所有工作组和计算机； 2.利用了win2k的net send 功能。可以向对端直接发送桌面消息，对端不 用有该程序； 3.可以查看对方的共享资源； 4.可以直接登录对方计算机，可以建立空连接； 5.可以点对点的进行语音通话； 6.可以匿名发送消息； 7.可以传送文件，（最好是小于10M的文件，这个功能还没有优化好）；-main functions : 1. LAN can search all the working group and the computer; 2. Win2k use of the net send function. To be sent directly to end desktop news is not right side of the proceedings; 3. View can share each other's resources; 4. The other side can be directly logged in the computer, we can establish air links; 5. Could the point-to-point voice calls; 6. Anonymous information can be sent; 7. documents can be transmitted, (preferably less than 10M of the document, and the optimization feature is not good); Platform: |
Size: 1079530 |
Author:凉凉 |
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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: |
Size: 16633 |
Author:张正 |
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Description: 主要功能： 1.可以搜索局域网内的所有工作组和计算机； 2.利用了win2k的net send 功能。可以向对端直接发送桌面消息，对端不 用有该程序； 3.可以查看对方的共享资源； 4.可以直接登录对方计算机，可以建立空连接； 5.可以点对点的进行语音通话； 6.可以匿名发送消息； 7.可以传送文件，（最好是小于10M的文件，这个功能还没有优化好）；-main functions : 1. LAN can search all the working group and the computer; 2. Win2k use of the net send function. To be sent directly to end desktop news is not right side of the proceedings; 3. View can share each other's resources; 4. The other side can be directly logged in the computer, we can establish air links; 5. Could the point-to-point voice calls; 6. Anonymous information can be sent; 7. documents can be transmitted, (preferably less than 10M of the document, and the optimization feature is not good); Platform: |
Size: 1079296 |
Author:凉凉 |
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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: |
Size: 16384 |
Author: |
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Description: pso算法的代码，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，-PSO algorithm code is based on an iterative optimization tools. Initialize the system for a group of random solutions, through iterative search for the optimal values, Platform: |
Size: 128000 |
Author:张林 |
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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: 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: 介绍用于光纤通信的速率为2.5 Gb/s的高速RS(255,239)译码器设计。对输入信号中可能出现的超
出译码器纠错能力的误码可进行检测判断,保证了误码不扩散。对译码器中大量使用的有限域乘法器进行了优化设计,尤其对并行钱氏搜索电路中的乘法器采用了按组优化设计方法,与直接实现方法相比,复杂度降低了45 -For optical fiber is introduced at a rate of 2.5 Gb/s (255239) of the high speed RS decoder design. Of the input signal of possible super
Out of the error correction decoder ability can detect judgment, to ensure the error non-proliferation. To use a lot of decoder limited domain on time-multiplier, the optimization design, especially for parallel once in the circuit on time-multiplier search by the group of optimization design method, and the direct method, compared to 45 lower complexity
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Author:孟君 |
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Description: Abstract：An improved GSO (Group Search Optimizer)Algorithm with predictive model is introduced in this paper．
MATLAB implementation of the improved Group Search Optimizer Al gorithm is described in detail．This paper introduced
the concept of function optimization and apphed the im proved algorithm to a function optimization example． Platform: |
Size: 4096 |
Author:瞿佳 |
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Description: 易思ESPCMS企业网站管理系统采用PHP5+MySQL5进行开发，它具有操作简单、功能强大、稳定性好、扩展性及安全性强、二次开发及后期维护方便，可以帮您迅速、轻松地构建起一个强大专业的企业网站。内置3GWAP手机网站、企业群站、模型字段自定义、SEO搜索优化、静态页生成、评论留言、订购、询价、会员、邮件订阅、邮件群发、广告、统计、自助表单等常见企业网站基本功能，通过灵活的插件机制还能扩展更多应用。-Easy the thinking ESPCMS enterprise website management system using PHP5+MySQL5 development, it has a simple operation, powerful, good stability, scalability and security, convenient secondary development and post-maintenance, can help you quickly and easily build a powerful professional corporate website. Built-in 3GWAP mobile site enterprises station group, model field custom, SEO search optimization, static page generation, Comments, ordering, Inquiry, Member, e-mail subscribers, mass mailing, advertising, statistics, buffet form common enterprise The basic functions of the website, but also extended more applications through a flexible plug-in mechanism. Platform: |
Size: 3975168 |
Author:刁红晨 |
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Description: 电力系统无功优化对确保电力系统优化运行具有重要作用,它直接关系到电力系统运行的安全性与经济性。在已有研究成果的基础上,提出了单目标／多目标的导向搜索算法与单目标／多目标的动态多群体自适应差分进化算法,对电力系统静态单目标无功优化、静态多目标无功优化、动态单目标无功优化、动态多目标无功优化、典型函数优化等问题进行了深入的研究和探讨。-Reactive power optimization to ensure the optimal operation of the power system plays an important role, it is directly related to the operation of the power system security and economy. On the basis of existing research results on the proposed single-objective/multiple targets with a single goal-oriented search algorithm adaptive differential dynamic multi-group/multi-objective evolutionary algorithm for power system static single objective reactive power optimization, static multi-objective without power optimization, dynamic single objective reactive power optimization, dynamic multi-objective optimization of reactive power, the typical function optimization problems in-depth study and discussion. Platform: |
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Author:杰 |
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Description: 粒子群算法（PSO）是一种基于群体的随机优化技术。与其它基于群体的进化算法相比，它们均初始化为一组随机解，通过迭代搜寻最优解。不同的是：进化计算遵循适者生存原则，而PSO模拟社会。将每个可能产生的解表述为群中的一个微粒，每个微粒都具有自己的位置向量和速度向量，以及一个由目标函数决定的适应度。所有微粒在搜索空间中以一定速度飞行，通过追随当前搜索到的最优值来寻找全局最优值。 -Particle swarm optimization (PSO) is a kind of stochastic optimization technique based on population. Compared with other evolutionary algorithms based on the group, they are initialized to a set of random solutions. The difference is: follow the principle of survival of the fittest evolutionary computation, and PSO simulation of society. Each of the possible solutions is expressed as a particle in the swarm, each particle has its own position vector and velocity vector, and the fitness of a target is determined by the target function. All particles in the search space to a certain speed, by following the current search to find the optimal value to find the global optimal value. Platform: |
Size: 3072 |
Author:Wang |
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Description: 工作原理是通过模拟自然界中生物进化的过程，设计相应的进化算子和操作，来解决复杂的实际问题，是一种建立在自然选择和遗传学基础上的搜索寻优算法。它从一组随机产生的种群开始，这个种群由经过基因编码的一定数量的个体组成，按照适者生存和优胜劣汰的规则，通过比较每个个体适应度的大小，选择适应度较大的个体进行交叉、变异，产生的新一代更适应环境的种群参与进化。通过一代一代不断的繁衍进化，最终得到最适应环境的个体，即得到问题的最优解。-Works by simulating the process of biological evolution in nature, design corresponding evolution operators and operations, to solve complex practical problems, is a search optimization algorithm based on natural selection and genetic basis. It is a group of the population randomly generated the beginning of this population by a gene coding for a certain number of individual composition, in accordance with the rules of survival of the fittest and survival of the fittest, by comparing the size of each individual fitness, choose the larger individuals fitness crossover and mutation, a new generation of better adapted populations produce environmental participate evolution. Through continuous breeding generations of evolution, finally get most individuals adapt to the environment, to obtain the optimal solution. Platform: |
Size: 499712 |
Author:杨文军 |
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Description: 一个基于matlab的GSO(群搜索)寻优算法例程，通过修改适应度函数可以完成不同的寻优任务，可用于开发改进算法或与其他智能优化算法进行对比。-A matlab-based GSO (group search) algorithm optimization routines, by modifying the fitness function optimization can perform different tasks that can be used to develop improved algorithms or other optimization algorithms and intelligent comparison. Platform: |
Size: 393216 |
Author:Edward.J |
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Description: 遗传算法（Genetic Algorithms，简称 GA）是一种基于自然选择原理和自然遗传机
制的搜索（寻优）算法，它是模拟自然界中的生命进化机制，在人工系统中实现特定目
标的优化。遗传算法的实质是通过群体搜索技术，根据适者生存的原则逐代进化，最终
得到最优解或准最优解。它必须做以下操作：初始群体的产生、求每一个体的适应度、
根据适者生存的原则选择优良个体、被选出的优良个体两两配对，通过随机交叉其染色
体的基因并随机变异某些染色体的基因后生成下一代群体，按此方法使群体逐代进化，
直到满足进化终止条件。(可用于路径优化)(Genetic Algorithms (GA) is a search algorithm based on natural selection principle and natural genetic mechanism. It simulates the mechanism of life evolution in nature and achieves the optimization of specific targets in artificial system. The essence of the genetic algorithm is by the group search technology, according to the principle of survival of the fittest, and finally get the optimal solution or the quasi optimal solution. It must do the following: the generation of initial population, for each individual to adapt to the excellent individual 22 degrees, according to the principle of survival of the fittest, select excellent individuals selected by random chromosome pairing, cross gene and random mutation of some genes on the next generation after generation, according to this method makes the group from generation to generation until the termination condition of evolution, evolution.(it can be used for Path optimization)) Platform: |
Size: 1024 |
Author:Arriettyrain |
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Search - group search optimization