Description: 粒子群算法与遗传算法用于优化的问题求解,可以解决一些-Particle Swarm Optimization and Genetic Algorithms for optimization problem solving, you can solve some Platform: |
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Author:tiger |
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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: |
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Author:sky |
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Description: 一系列好用的用户友好的启发式优化算法，包括非自适应算法，基于模拟退火算法的种群算法，基本遗传算法，差分进化算法以及粒子群优化算法。此外，也包括神圣算法，它利用了所有这些优化算子，虽然有时交换种群之间的不同算法。-A nice set of user-friendly heuristic optimizers. Included are a non-adaptive, population based Simulated Annealing algorithm, a basic Genetic Algorithm, (transversal) Differential Evolution algorithm and Particle Swarm Optimization algorithm. Also, the GODLIKE-algorithm is included, which simply uses all of these optimizers while occasionally swapping populations between the different algorithms.
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Size: 26624 |
Author:竹子的信仰 |
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Description: 这是一个经过改进的PSO算法，是用FORTRAN语言编写的，因为此语言计算速度快，适合PSO的应用，收敛速度明显加快，并且这是改优化后的PSO程序，比标准的速度快。-This is an improved PSO algorithm, are used FORTRAN language, because this language computing speed, suitable PSO applications, significantly speeding up the convergence rate, and change This is the optimized PSO procedures, faster than the standard. Platform: |
Size: 1024 |
Author:xin |
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Description: 关于一些算法中如何生成新成员的选择方法，粒子群算法，遗传算法等算法可以用。-How about some algorithm to generate a new member of the selection method, particle swarm optimization, genetic algorithms and other algorithms can be used. Platform: |
Size: 5120 |
Author:wang |
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Description: 此包含有遗传算法、粒子群算法、BP算法优化对角递归神经网络的MATLAB程序-This includes genetic algorithms, particle swarm optimization, BP algorithm for diagonal recurrent neural network of the MATLAB program Platform: |
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Author: |
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Description: 用Java实现的进化算法包。包括遗传算法、粒子群算法、memetic算法和进化策略算法。-evolutionary-algorithm
Evolutionary Algorithm package implemented using Java.
The package serves as a foundation class library, supporting the implementation many variants of Evolutionary Algorithms, currently including Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Memetic Algorithm (MA), Evolution Strategy (ES).
Highlighted features
· Support both binary & real-coded string representations of solution
· Operator-based design for flexibility
· EA Operators: Selection, Crossover, Mutation, Move operators in PSO & and the adaptive scheme in EA
· Individual learning: Davidon–Fletcher–Powell (DFP) and Davies, Swann, and Campey with Gram-Schmidt orthogonalization (DSCG) strategies and Random Mutation Hill-climbing (RMHC)
In addition, algorithm pipeline which is specified by XML file is also provided for practitioner to configure & design evolutionary algorithms at ease. User can edit runtime & algorithm parameters in the configuration file (XML) & issue the co Platform: |
Size: 104448 |
Author:陈雷 |
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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: 除了蚁群算法，可用于PID参数优化的智能算法还有很多，比如遗传算法、模拟退火算法、粒子群算法、人工鱼群算法，等等。-In addition to ant colony algorithm can be used to optimize the PID parameters there are many intelligent algorithms, such as genetic algorithms, simulated annealing algorithm, particle swarm optimization, artificial fish-swarm algorithm, and so on. Platform: |
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Author:张望 |
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Description: This chapter provides two recent algorithms for evolutionary optimization – well known as particle
swarm optimization (PSO) and differential evolution (DE). Platform: |
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Author:regenrentgen |
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Description: 介绍了利用遗传算法，优化稀布阵列的阵元的排布-Introduced the use of genetic algorithms and particle swarm optimization, optimization thinned array element array arranged Platform: |
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Author:孙伟 |
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Description: 粒子群优化算法的JAVA实现,说明：算法为了演示功能，所以没有优化，没有异常处理等，仅作演示用。-Particle swarm optimization algorithm JAVA, Description: Algorithms for presentation capabilities, so no optimization, no exception handling, etc., only for demonstration purposes. Platform: |
Size: 2048 |
Author:gy |
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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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Description: A novel method based on a combination of the Extended Kalman Filter (EKF) with Particle Swarm Optimization (PSO) to estimate the speed and rotor flux of an induction motor driveis presented. The proposed method will be performed in two steps. As a first step, the covariance matrices of state noise and measurement noise will be optimized in an off-line manner by the PSO algorithm. As a second step, the optimal values of the above covariance matrices are injected in our speed-rotor flux estimation loop (on-line).Computer simulations of the speed and rotor-flux estimation have been performed in order to investigate the effectiveness of the proposed method. Simulations and comparison with genetic algorithms (GAs) show that the results are very encouraging and achieve good performances. Platform: |
Size: 665750 |
Author:pudn0507@yahoo.fr |
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Search - particle swarm optimization algorithms