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[AI-NN-PRQACSMATLAB

Description: use swarm intelligence algorithm to slove travelling sales man problems in matlab-use swarm intelligence algorithm to slove traveling sales man problems in Matlab
Platform: | Size: 1024 | Author: william | Hits:

[AI-NN-PRantnet-4.0-src

Description: use swarm intelligence to simulate network routings in omnet-use swarm intelligence to simulate networ k routings in omnet
Platform: | Size: 69632 | Author: william | Hits:

[source in ebookcdos

Description: 国外名著《Swarm Intelligence》一书的配套代码,C语言编写。-abroad masterpiece "Swarm Intelligence," a book supporting code, C language.
Platform: | Size: 62464 | Author: 布拉德 | Hits:

[matlabASM-2.2swarm

Description: 人工智能的matlab程序,swarm群只能算法演示的源代码。-artificial intelligence Matlab procedures swarm group can demonstrate the algorithm source code.
Platform: | Size: 183296 | Author: appli | Hits:

[Mathimatics-Numerical algorithmsPSOGA

Description: 改进的群体智能算法,简称PSO算法,包括C和matlab两种版本-Improved swarm intelligence algorithm, referred to as PSO algorithm, including two versions of C and matlab
Platform: | Size: 79872 | Author: 赵栓峰 | Hits:

[Otherimproving_the_performance_of_pso_using_adaptive_de

Description: Swarm intelligence algorithms are based on natural behaviors. Particle swarm optimization (PSO) is a stochastic search and optimization tool. Changes in the PSO parameters, namely the inertia weight and the cognitive and social acceleration constants, affect the performance of the search process. This paper presents a novel method to dynamically change the values of these parameters during the search. Adaptive critic design (ACD) has been applied for dynamically changing the values of the PSO parameters.-Swarm intelligence algorithms are based on naturalbehaviors. Particle swarm optimization (PSO) is astochastic search and optimization tool. Changes in thePSO parameters, namely the inertia weight and thecognitive and social acceleration constants, affect theperformance of the search process. This paper presents anovel method to dynamically change the values of theseparameters during the search. Adaptive critic design (ACD) has been applied for dynamically changing thevalues of the PSO parameters.
Platform: | Size: 365568 | Author: sky | Hits:

[OtherSwarm_Intelligent_Systems

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: | Size: 5972992 | Author: dh | Hits:

[OtherSwarm_Intelligent_Systems-Springer

Description: Swarm intelligence is an innovative computational way to solving hard problems. This discipline is inspired by the behavior of social insects such as fish schools and bird flocks and colonies of ants, termites, bees and wasps. In general, this is done by mimicking the behavior of the biological creatures within their swarms and colonies.
Platform: | Size: 5974016 | Author: 黄先生 | Hits:

[File Formatjumping_frog

Description: a new swarm intelligence optimization method for discrete problems.
Platform: | Size: 173056 | Author: seda | Hits:

[OtherSwarmIntelligence

Description: 群体智能,高清版本。国际该领域大牛的作品。对搞智能计算和优化方面的朋友应该是非常有用的。-Swarm Intelligence. To engage in intelligent computing and optimization of a friend should be very useful.
Platform: | Size: 8741888 | Author: 郑林涛 | Hits:

[Otherswarm-intelligence

Description: swarm intelligence from natural to artificial systems
Platform: | Size: 17945600 | Author: mon | Hits:

[Software Engineeringijrte0101611615

Description: IMAGE SEGMENTATION USING ACO: THE CONCEPT OF SWARM INTELLIGENCE
Platform: | Size: 1008640 | Author: Katty1388 | Hits:

[Mathimatics-Numerical algorithmsComputational-Intelligence-Paradigms-Theory-a-App

Description: The aim of this book is to furnish some theoretical concepts and to sketch a general framework for computational intelligence paradigms such as artificial neural networks, fuzzy systems, evolutionary computation, genetic algorithms, genetic programming, and swarm intelligence. The book includes a large number of intelligent computing methodologies and algorithms employed in computational intelligence research. The book also offers a set of solved programming examples related to computational intelligence paradigms using MATLAB software. Additionally, such examples can be repeated under the same conditions, using different data sets. Researchers, academicians, and students in computational intelligence can use this book to verify their ideas related to evolution dynamics, self-organization, natural and artificial morphogenesis, emergent collective behaviors, swarm intelligence, evolutionary strategies, genetic programming, and evolution of social behaviors.
Platform: | Size: 6013952 | Author: Umar | Hits:

[Special EffectsParticle-swarm-optimization

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: | Hits:

[AI-NN-PRswarm-intelligence-algorithm

Description: 压缩文件内是一本有关群体智能算法的中文专著,文中详细介绍了粒子群优化算法的原理,并用案例对其进行了详细讲解。-The compressed file is a monograph on swarm intelligence algorithms Chinese paper describes in detail the principle of the particle swarm optimization algorithm, and a case be explained in detail.
Platform: | Size: 1839104 | Author: ocean | Hits:

[OtherSwarm-intelligence-o

Description:  讨论四种群体智能优化算法———蚁群算法、微粒群算法、人工鱼群算法和混合蛙跳算法 ,对其算法的 原理、发展及应用进行了综述。提出了群体智能优化算法统一框架模式 ,并对群体智能优化算法进一步发展进行 了讨论。 - Discuss four swarm intelligence optimization algorithm--- ant colony algorithm, particle swarm optimization, artificial fish swarm algorithm and shuffled frog leaping algorithm, their algorithm theory, development and application are reviewed. Swarm intelligence optimization algorithm proposed unified framework model, and the further development of swarm intelligence optimization algorithms are discussed.
Platform: | Size: 396288 | Author: chenchen | Hits:

[source in ebookSwarm-Intelligence

Description: Swarm Intelligence相关算法,包含算法源代码和文档-Swarm Intelligence related algorithms, including the algorithm source code and documentation
Platform: | Size: 1305600 | Author: lwk | Hits:

[Software EngineeringA-Swarm-Intelligence-Algorithm

Description: 联合稀疏恢复的Swarm算法,在基本particle swarm optimization (PSO)算法基础上进行改进-Inspired by particle swarm optimization (PSO) algorithm and some sparse recovery algorithms, a novel swarm intelligence algorithm called M-SISR is proposed to solve the problem. In M-SISR, the initial positions of the swarm are designed using the-thresholding algorithm, and the update strategy is designed using the ideas of PSO and some sparse recovery algorithms. Theoretical analysis shows the good property of the update strategy, and numerical simulations on random Gaussian data illustrate the efficiency of M-SISR.
Platform: | Size: 1249280 | Author: bigbigtom | Hits:

[OtherChicken Swarm Optimization Algorithm

Description: 鸡群算法是一种全新的群智能算法,具有简单,良好的可扩展性,(Chicken swarm algorithm is a new swarm intelligence algorithm with simple and good scalability,)
Platform: | Size: 192512 | Author: 奋斗小孩 | Hits:

[Mathimatics-Numerical algorithmsnichingparticle-swarm-optimization

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: | Size: 5953536 | Author: dreamer | Hits:
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