Search - evolutionary algorithms

Search - evolutionary algorithms - List

[Mathimatics-Numerical algorithms] DLA DL : 0: 在分形几何里面，非常重要的一部分内容就是分形演化算法。这个模块提供的是用DLA模型模拟植物生长的算法。-Fractal geometry in the inside, a very important part of the content is the evolutionary algorithm fractal. The module is provided by DLA model simulation of plant growth algorithms.
Date : 2025-12-28 Size : 1.83mb User : wang
[Mathimatics-Numerical algorithms] Particle DL : 0: 这是导师留给我的用JAVA写的进化算法,比较经典,请审核.-This is left to my mentors used to write JAVA evolutionary algorithms, the classical comparison, please review.
Date : 2025-12-28 Size : 1kb User : 强
[Mathimatics-Numerical algorithms] 080502 DL : 0: 基于MATLAB的蚁群算法仿真研究：介绍了基于MATLAB的蚁群算法仿真研究。对佛罗里达州六城市旅行商问题进行了MATLAB仿真，计算结果显示，作为新型进化算法，蚁群算法能够解决复杂组合优化问题。-Ant colony algorithm based on MATLAB Simulation: This paper introduces the ant colony algorithm based on the MATLAB simulation. Six Cities of Florida conducted a traveling salesman problem MATLAB simulation, the calculation results show that, as a new type of evolutionary algorithms, ant colony algorithm to solve complex combinatorial optimization problem.
Date : 2025-12-28 Size : 280kb User : 张学利
[Mathimatics-Numerical algorithms] HierarchicalBayesianOptimizationAlgorithm DL : 0: Hierarchical Bayesian Optimization Algorithm: Toward a New Generation of Evolutionary Algorithms
Date : 2025-12-28 Size : 1.75mb User : 傲天
[Mathimatics-Numerical algorithms] GA_NSGA-II DL : 0: Develop the NSGA-II or SPEA2 multiobjective evolutionary algorithms to solve the multiobjective optimization problems.-Develop the NSGA-II or SPEA2 multiobjective evolutionary algorithms to solve the multiobjective optimization problems.
Date : 2025-12-28 Size : 3kb User : Su Yu-Jiun
[Mathimatics-Numerical algorithms] SocialEvolutionaryProgramming DL : 1: 社会演化算法是一种新型的进化算法。这是基于社会演化算法的PID控制器参数整定的程序。学习遗传算法和进化算法的都有借鉴作用- Social Evolutionary Programming (SEP) to solve this problem. SEP is developed from Genetic Algorithm (GA), inherits the advantage of GA and other algorithms, and has better convergence rate and the computation efficiency than GA.
Date : 2025-12-28 Size : 8kb User : wangjin
[Mathimatics-Numerical algorithms] Computational-Intelligence-Paradigms-Theory-a-App DL : 0: 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.
Date : 2025-12-28 Size : 5.74mb User : Umar
[Mathimatics-Numerical algorithms] improve DL : 0: 基于进化规划的FCMBP模糊聚类改进方法Based on Evolutionary Programming FCMBP fuzzy clustering method to improve-Based on Evolutionary Programming FCMBP fuzzy clustering method to improve
Date : 2025-12-28 Size : 785kb User :
[Mathimatics-Numerical algorithms] evolutionary-algorithms DL : 0: 多目标遗传算法进展，多目标遗传算法进展，-Advances in multi-objective evolutionary algorithms
Date : 2025-12-28 Size : 138kb User : leichenjian
[Mathimatics-Numerical algorithms] 13 DL : 0: 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。 PSO模拟社会采用了以下三条简单规则对粒子个体进行操作：①飞离最近的个体，以避免碰撞。②飞向目标。③飞向群体的中心。这是粒子群算法的基本概念之一。粒子群算法其基本思想是受许多鸟类的群体行为进行建模与仿真研究结果的启发-Particle swarm optimization (PSO) is a population based stochastic optimization techniques. Based on evolutionary algorithms compared with other groups, they are initialized to a random solution, iterative search through optimal solution. The difference is: the principle of survival of the fittest evolutionary computation to follow, while PSO simulation community. The potential of each solution expressed as a group of particles, each particle has its own position vector and the velocity vector, and a fitness determined by the objective function. All particles in the search space at a constant speed flight, by following the current search to find the optimal values of the global optimum. PSO simulation community has adopted the following three simple rules for the operation of individual particles: ① recently departed individuals, in order to avoid collisions. ② to the target. ③ fly to center groups. This is one of the basic concepts of particle swarm algorithm. PSO algori
Date : 2025-12-28 Size : 6kb User : hhhh
[Mathimatics-Numerical algorithms] nichingparticle-swarm-optimization DL : 0: 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)
Date : 2025-12-28 Size : 5.68mb User : dreamer