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ycthjhsf
- 遗传退火进化算法, 遗传退火进化算法-Genetic annealing evolutionary algorithm, genetic annealing evolutionary algorithm
ANNandSAA
- 用matlab编写的遗传算法和模拟退火程序-Matlab prepared using genetic algorithms and simulated annealing procedures
geneticalgorithm
- 结合离散时间系统最优控制问题,提出一种新的混合算法.该算法是在遗传操作中嵌入模 拟退火算子,有效地结合了遗传算法隐含并行与模拟退火算法全局寻优的特点 -By embedding simulated annealing operator into genetic algorithm, a hybrid algorithm is put forward, which assimilates advantages ofboth genetic algorithm and simulated
gafuzzymatlab
- 模拟退火，禁忌搜索，遗传算法，神经网络-MATLAB程序合集 -Simulated annealing, tabu search, genetic algorithm, neural network-MATLAB collection procedures simulated annealing, tabu search, genetic algorithm, neural network-MATLAB collection procedures
genetic
- 改C程序结合了遗传算法和模拟退火算法的思想，能求出网络图中各工序的最优开工时间和工程的收益的净现值。-C program to a combination of genetic algorithms and simulated annealing algorithm can find the network map to start the process of the optimal time and the project' s net present value of earning
BP
- 基于BP神经网络算法的研究，主要比较了模拟退火算法、遗传算法、P神经网络的区别，提出了一种比较优化的BP算法-the research for BP
GODLIKE
- 遗传算法与模拟退火,粒子群算法的结合与比较实验.稍微修改就可以学习应用-Genetic algorithms and simulated annealing, particle swarm optimization algorithm and comparison with experiment. A slight modification can learn the application of
psoandimprovedpso
- 基本粒子群优化算法和改进粒子群优化算法程序，包括：用基本粒子群算法求解无约束优化问题，用带压缩因子的粒子群算法求解无约束优化问题，用线性递减权重粒子群优化算法求解无约束优化问题，用自适应权重粒子群优化算法求解无约束优化问题，用随机权重粒子群优化算法求解无约束优化问题，用学习因子同步变化的粒子群优化算法求解无约束优化问题，用学习因子异步变化的粒子群优化算法求解无约束优化问题，用二阶粒子群优化算法求解无约束优化问题，用二阶振荡粒子群优化算法求解无约束优化问题，用混沌粒子群优化算法求解无约束优化问题，
GASA
- 基于遗传模拟退火和Otsu法的图像分割。采用一种基于模拟退火算法(SA)的混合遗传算法(GASA),来进行Otsu方法选择阈值，其中进行求解时是非线性的遗传算法（GA）的应用优化了求阈值过程，并尽可能地减少其运算量,而加入SA则避免了遗传算法(GA)常见的早熟收敛现象,从而实现有效简单的图像分割。 -adopt hybrid genetic algorithm(GASA) based on simulated annealing algorithm,choose threshold by O
TSP
- 有遗传算法及模拟退火算法对TSP的应用，有框架窗口。-A genetic algorithm and simulated annealing algorithm for TSP applications, there are frame window.
PIDcontrowithAOC
- 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
Theadvancedcomparisonalgorithmlecture
- 在本讲义中，我们将着重讲述一些数学建模中常用的算法，包括神经网络算法、遗传算 法、模拟退火算法和模糊数学方法。用这些算法可以较容易地解决一些很复杂的，常规算法很难解决的问题。-In this lecture, we will focus on about a number of commonly used mathematical modeling algorithms, including neural network algorithm, genetic algorithm Meth
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
GA_test
- 遗传算法：二进制、单点交叉、单点变异、轮盘赌、模拟退火(默认无)、最优个体保留(默认无)-Genetic algorithm: binary, single-point crossover, single-point mutation, roulette, simulated annealing (default no), best individual reservations (default no)
monituihuo_GA
- 用模拟退火算法和遗传算法的混合算法求解旅行商问题-By simulated annealing algorithm and genetic algorithm hybrid algorithm for Traveling Salesman Problems
xqw0910
- brush developed in delphi ·Improved component for work with ·Improve DBGrid from EhLib. Many f ·Delphi 的StringGrid无法嵌入ComboB ·一个相当不错的皮肤源码 ·制作API钩子,截获API的源码 ·漂亮的delphi界面控件 ·远程桌面，服务端+客户端 ·DELPHI办公全套管理系统 ·针对 UDP 通讯协议的 Socket 构件， ·获取
many-methods-to-solve-TSP
- 多种方式求解TSP问题，有遗传算法，A*算法，D算法，模拟退火，神经网络等-A variety of ways to solve TSP problem, a genetic algorithm, A* algorithm, D algorithm, simulated annealing, neural networks
simulated-annealing-genetic-method
- 一种新型的算法，将模拟退火法和遗传算法相结合，用于求解预测问题-A new algorithm, simulated annealing and genetic algorithm are combined to solve the prediction problem for
gmt
- 此为遗传算法和模拟退火算法相结合的一个方法，可实现对函数的优化-This is the genetic algorithm and simulated annealing algorithm, a combination of methods, the optimization function can be realized