搜索资源列表
模拟退火c++的算法程序
- 模拟退火c++的算法程序,广泛应用于最优化、运筹学、人工智能、遗传算法等领域,具有很好的学习价值-simulated annealing algorithm procedures, the most widely used optimization, operations research, artificial intelligence, genetic algorithms and other areas of learning is very good value
AGP-NNBP
- 遗传模拟退火算法通用源程序 给定群体规模,群体,种群,初始温度-genetic simulated annealing definitive source given population size, population, population, the initial temperature
MCRGSA
- MCRGSA------组播路由问题遗传模拟退火算法 %M-----------遗传算法进化代数 %N-----------种群规模,取偶数 %Pm----------变异概率调节参数 %K-----------同一温度下状态跳转次数 %t0----------初始温度 %alpha-------降温系数 %beta--------浓度均衡系数 %ROUTES------备选路径集 %Num---------到各节点的备选路径数目 %Cost-------
TSPTravelingsalesmanproblem
- 完全图哈密尔顿圈的遗传模拟退火算法matlab通用源程序拟退火算法解0-1背包问题MATLAB源代码 -complete graph Hamilton Circle genetic simulated annealing Matlab to be definitive source solution annealing 0 - a knapsack problem MATLAB source code
aaayichuan
- 遗传模拟退火算法在弹药装载中的应用研究 PDF文挡,相当经典,供大家分享
ImageSegmentation
- 基于马尔可夫随机场的遗传模拟退火算法用于图像分割,研究进化算法用于图像分割的同志可以得到启发
geneticalgorithmandsimulatedannealingalgorithm
- 建立了多约束条件车辆路径问题的数学模型和求解流程先采用最近插入法生成初始解然后基于遗传算法和模拟退火算法改进初始解-The establishment of a multi-vehicle routing problem with constraint model and solution process first insertion generated by the recent initial solution and based on genetic algorithm and simu
taiozhanbei
- 用遗传算法和模拟退火算法解决旅行商方面的问题-The genetic algorithm and simulated annealing algorithm to solve traveling salesman problems
TSP-based-on-improved-pso
- 基于对粒子群优化算法原理的分析,实现了一种基于TSP的改进的粒子群优化算法:求解TSP的混合粒子群算法,结合遗传算法、蚁群算法和模拟退火算法的思想来解决TSP问题。-Particle swarm optimization based on the principle of the analysis, implemented based on TSP, improved particle swarm optimization algorithm: solving the TSP hybrid pa
image_segmentation
- 遗传模拟退火图像分割算法,对学习图像分割的童鞋们很有帮助,分割效果也很好~-Genetic simulated annealing algorithm for image segmentation, image segmentation of the study of children' s shoes are very helpful, segmentation is also very good ~
精通MATLAB智能算法(2015代码)
- 这是一个智能算法程序吧,里面有模拟退火算法,遗传算法,粒子群算法等等,希望这些算法对初学者来说有用处。(This program is an intelligent algorithm, simulated annealing algorithm, genetic algorithm, particle swarm optimization (pso) algorithm and so on, hope that the algorithm is useful for beginners.)
Matlab十大算法源代码
- Floyd算法,概率算法,类比法,蒙特卡洛,神经网络,贪婪算法,模拟退火算法,灰色预测,遗传算法等(Floyd algorithm, probability algorithm, analogy method, Monte Carlo, neural network, greedy algorithm, simulated annealing algorithm, grey prediction, genetic algorithm, etc.)
智能算法
- 智能算法,含有遗传算法、模拟退火算法、BP神经网络优化、免疫算法、粒子群算法、蚁群算法等智能算法,MATLAB亲测可用。(Intelligent algorithm, including genetic algorithm, simulated annealing algorithm, BP neural network optimization, immune algorithm, particle swarm algorithm, ant colony algorithm and other
[原创]模拟退火算法论文集
- 牛顿迭代求根遗传退火算法的APP打包,十分实用,适合新手(The Numerical Phenomenon in Newton's Iterative Method for Solving Complex Polynomials)
遗传算法处理NURBS曲线逼近(Matlab实现)
- 在Matlab平台上采用将模拟退火算法及遗传算法相结合的曲线拟合方法,实现以任意次数、任意顶点数的非均匀有理B样条(NURBS)曲线逼近给定测量点序列(On the Matlab platform, we use the curve fitting method combining simulated annealing algorithm and genetic algorithm to achieve the sequence of a given measurement point wit
遗传算法退火算法
- 利用MATLAB实现模拟退火算法的在各实际情况中的应用(The application of simulated annealing algorithm.)
Annealing algorithm
- 利用退火算法实现无人机路径巡航,但是效果比不上遗传算法。(The annealing algorithm is used to realize the route cruise of UAV.)
30个智能算法模型
- 1-8遗传算法,9 多目标Pareto最优解搜索算法,10 基于多目标Pareto的二维背包搜索算法,11-12免疫算法,13-17粒子群算法,18鱼群算法,19-21模拟退火算法,22-24蚁群算法,25-27神经网络,28 支持向量机的分类,29 支持向量机的回归拟合,30 极限学习机的回归拟合及分类(1-8 genetic algorithm, 9 multi-objective Pareto optimal solution search algorithm, 10 multi-obje
111
- 用于求解带时间窗的多车场的配送路径优化问题,即vrp问题,算法是基于模拟退火算法和遗传算法的混合算法(The algorithm is a hybrid algorithm based on simulated annealing algorithm and genetic algorithm, which is used to solve the distribution path optimization problem of multi depot with time window)
粒子群算法
- 粒子群算法,也称粒子群优化算法或鸟群觅食算法(Particle Swarm Optimization),缩写为 PSO, 是近年来由J. Kennedy和R. C. Eberhart等 开发的一种新的进化算法(Evolutionary Algorithm - EA)。PSO 算法属于进化算法的一种,和模拟退火算法相似,它也是从随机解出发,通过迭代寻找最优解,它也是通过适应度来评价解的品质,但它比遗传算法规则更为简单,它没有遗传算法的"交叉"(Crossover) 和"