Description: 人工鱼群算法解决旅行商问题,这是在当前互联网上唯一的一个,这个是我自己编的,保证通过-Artificial fish-swarm algorithm to solve traveling salesman problem, which is in the current Internet, the only one, this is my own, and to ensure through Platform: |
Size: 4096 |
Author:有偿编程，挣点生活费 |
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Description: 组合优化问题的人工鱼群算法应用
通过模仿鱼类的行为方式,提出了一种基于动物自治体的优化方法—人工鱼群算法(Artificial Fish- school Al2
gorithm) ,并将其用于组合优化问题的求解. 介绍了该算法在此类问题求解中的距离、邻域等概念,给出了具体的实
现方法. 最后以TSP 问题为例对该算法进行仿真测试. 结果表明它具有快速收敛的能力.-Combinatorial optimization problems through the application of artificial fish-swarm algorithm to imitate the behavior of fish, an animal-based self-governing body of the optimization method- artificial fish-swarm algorithm (Artificial Fish-school Al2gorithm), and their use for solving combinatorial optimization problems . Introduction of the algorithm for solving such problems in the distance, the concept of neighborhood is given a specific method. Finally to TSP as an example of the algorithm simulation tests. The results show that it has the ability to fast convergence. Platform: |
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Author:馨竹 |
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Description: 非常好的优化算法的书，详细介绍了蚁群算法和粒子群算法以及相关的matlab工具箱，讲了理论和应用给出了工具箱的下载地址。
Swarm intelligence is an innovative computational way to solve hard problems. In particular, particle swarm optimization, also commonly known as PSO, mimics the behavior of a swarm of insects or a school of fish. If one of the particle discovers a good path to food the rest of the swarm will be able to follow instantly even if they are far away in the swarm. Swarm behavior is modeled by particles in multidimensional space that have two characteristics: a position and a velocity. These particles wander around the hyperspace and remember the best position that they have discovered. They communicate good positions to each other and adjust their own position and velocity based on these good positions. -Optimization algorithm very good book, detailing the ant colony algorithm and particle swarm optimization and related matlab toolbox, talked about the theory and application are given toolbox download address. Swarm intelligence is an innovative computational way to solve hard problems. In particular, particle swarm optimization, also commonly known as PSO, mimics the behavior of a swarm of insects or a school of fish. If one of the particle discovers a good path to food the rest of the swarm will be able to follow instantly even if they are far away in the swarm. Swarm behavior is modeled by particles in multidimensional space that have two characteristics: a position and a velocity. These particles wander around the hyperspace and remember the best position that they have discovered. They communicate good positions to each other and adjust their own position and velocity based on these good positions. Platform: |
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Author:dh |
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Description: 这是一个关于人工鱼群算法的具体实例编程，算法用c实现，参数可以改动设置。包括人工鱼群流程图-This is a study on artificial fish-swarm algorithm specific examples of programming, algorithms using c realize, parameter settings can be changed. Including the flow chart of the artificial fish Platform: |
Size: 71680 |
Author:wang |
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Description: FSA人工鱼群算法用MATLAB编程实现。有很高的价值。体现了人工鱼群算法的特点。保证能运行。-FSA artificial fish-swarm algorithm with MATLAB Programming. Has a high value. Embodies the characteristics of artificial fish-swarm algorithm. Guarantee that it will run. Platform: |
Size: 2048 |
Author:zhangchuangye |
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Description: 关于鱼群算法的一个程序，希望对学习智能算法的朋友有所帮助。-Fish-swarm algorithm on a procedure, and they hope to learn from intelligent algorithm friend help. Platform: |
Size: 4096 |
Author:duweijie |
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Description: 摘 要:在分析人工鱼群算法存在不足的基础上,对人工鱼群算法加以改进,提出了一种改进型人工鱼群算
法。该算法提高了全局搜索能力和收敛速度,并用于求解具有变量边界约束的非线性复杂函数最优化问题。
仿真结果表明,改进后的人工鱼群算法具有精度高、搜索速度快等特点,是一种求解复杂函数全局最优化的智
能算法。
-Abstract: In analyzing the deficiencies of artificial fish-swarm algorithm based on improved artificial fish-swarm algorithm, an improved artificial fish-swarm algorithm. The algorithm improve the global search ability and convergence speed, and used to solve the border with variables constrained nonlinear optimization problem of complex functions. The simulation results show that the improved artificial fish-swarm algorithm with high precision, fast search, etc., is a complex function for solving global optimization of the intelligent algorithm. Platform: |
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Author:duweijie |
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Description: ：群智能是一种仿生自然界动物昆虫觅食筑巢行为的新兴演化计算技术。目前主要的群智能优化算法有蚁群算法、微粒群算
法和人工鱼群算法。本文介绍了群智能算法的产生、发展和优点，并着力阐述了上述三种典型算法的基本原理，同时概述了各
算法的应用现状，最后提出了算法将来有待研究的内容。-: Swarm Intelligence is a kind of bionic nature nesting animals foraging behavior of insects emerging computing technology evolution. At present, the main group of intelligent optimization algorithms are ant colony algorithm, particle swarm optimization and artificial fish-swarm algorithm. This paper introduces the intelligent algorithm groups the emergence, development and benefits, and focus on the three basic principles of a typical algorithm, the algorithm also provides an overview of the application of the status quo, the end of the algorithm to be the future contents of the study. Platform: |
Size: 184320 |
Author:duweijie |
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Description: 摘 要:在分析人工鱼群算法存在不足的基础上,对人工鱼群算法加以改进,提出了一种改进型人工鱼群算
法。该算法提高了全局搜索能力和收敛速度,并用于求解具有变量边界约束的非线性复杂函数最优化问题。
仿真结果表明,改进后的人工鱼群算法具有精度高、搜索速度快等特点,是一种求解复杂函数全局最优化的智
能算法
-Abstract: In analyzing the deficiencies of artificial fish-swarm algorithm based on improved artificial fish-swarm algorithm, an improved artificial fish-swarm algorithm. The algorithm improve the global search ability and convergence speed, and used to solve the border with variables constrained nonlinear optimization problem of complex functions. The simulation results show that the improved artificial fish-swarm algorithm with high precision, fast search, etc., is a complex function for solving global optimization of the intelligent algorithm Platform: |
Size: 189440 |
Author:duweijie |
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Description: 关于人工鱼群算法的一个实例，可以实现所有的人工鱼的基本功能，是采用c开发的-Artificial fish-swarm algorithm on an instance, you can realize all the basic functions of the artificial fish is developed using c Platform: |
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Author:g |
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Description: 微粒群优化算法(Particle Swarm Optimization,PSO算法)源于鸟群和鱼群群体运
动行为的研究，是一种新的群体智能优化算法，是演化计算领域中的一个新的分支。它
的主要特点是原理简单、参数少、收敛速度较快，所需领域知识少。该算法的出现引起
了学者们极大的关注，已在函数优化、神经网络训练、组合优化、机器人路径规划等领
域获得了广泛应用，并取得了较好的效果。尽管粒子群优化算法发展近十年，但无论是
理论分析还是实践应用都尚未成熟，有大量的问题值得研究。
-Particle swarm optimization (Particle Swarm Optimization, PSO algorithm) from groups of birds and fish movement behavior, is a new swarm intelligence algorithm, in the field of evolutionary computation is a new branch. Its main feature is simple in principle, few parameters, convergence is faster, less domain knowledge required. The algorithm brought the scholars are of great concern, has been in function optimization, neural network training, combinatorial optimization, robot path planning has been widely used applications, and achieved good results. Despite the development of particle swarm optimization nearly a decade, but both theory and practice applications are not yet mature, a large number of issues worth studying. Platform: |
Size: 602112 |
Author:赵 |
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Description: 本程序为智能算法。遗传，粒子群，鱼群，蚁群等多种算法。以及一些实际案例-This program is intelligent algorithms. Genetic, particle swarm, fish, ant colony and many other algorithms. As well as some actual cases Platform: |
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Author:huairen |
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Description: 本文基于matlab开发环境，利用鱼群算法对30节点的电网进行无功优化-Reactive Power Optimization Based on fish swarm algorithm in 30 node grid Platform: |
Size: 6144 |
Author:sywhcsu |
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Description: c++语言实现鱼群算法，使用粒子群优化算法给出-Fish algorithm c++ language, the use of particle swarm optimization algorithm is given
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Author:秦时221207 |
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Description: 粒子群优化算起源于对鸟群、鱼群以及对某些社会行为的模拟，是一种基于群体智能的进化计算技术。而小生境技术则起源于遗传算法，这种方法能使基于群体的随机优化算法形成物种，从而使相应的优化算法具有发现多个最优解的能力。而多分类器集成技术则是通过多个分类器进行某种组合来决定最终的分类，以取得比单个分类器更好的性能。多分类器集成技术要求基元分类器不仅个体性能要好并且其差异度要大，这与小生境技术形成物种的能力具有很多内在的相似性。目前己经有研究者将小生境技术应用于多分类器集成，但由于传统的小生境技术仍然不完善，存在一些内在的陷，因而这些应用还不成熟和完善。
(Particle swarm optimization (partieleSwarmOptimization) originated in the birds, fish, and of a
Some simulation of social behavior, is a swarm intelligence-based evolutionary computing. The origin of the niche technology is In genetic algorithms, this method can make random optimization algorithm based on the formation of groups of species, so that the appropriate priority
Algorithm has the ability to find multiple optimal solutions. The integration technology of multiple classifiers is through multiple classifiers into
Some combination of the line to determine the final classification, in order to obtain better than a single classifier performance. Integration of multiple classifiers
Technical requirements for primitive classification is not only better individual performance and the difference to a large degree, which form a niche technology The ability of species has many inherent similarities. The researchers will now have a niche technology used in multisection
Class ens) Platform: |
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Author:dreamer |
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Search - swarm fish algorithm