搜索资源列表
sarose
- 模拟退火算法可求组合优化问题及连续优化问题的近似最优解。这里提供一个连续优化问题的例。-Simulated annealing algorithm for solving continuous optimization problems
annealing
- 模拟退火算法可求组合优化与连续优化的最优解，这里提供模拟退火算法一个组合优化的例-Combination of simulated annealing optimization and rectifiable continuous optimization of the optimal solution, which offers a combination of simulated annealing algorithm to optimize the patients
CS_Based_PR_CW_Radar
- 基于压缩感知的伪随机多相码连续波雷达，为了提高目标信息提取的有效性，采用模拟退火算法对波形进行优化。仿真结果表明了该方法的优越性。-To improve the effectiveness of targets information extraction, the waveform is optimized using Simulated Annealing (SA) algorithm.Simulation results demonstrate the merits of the prop
simulated-annealing-algorithm--cPP
- 模拟退火算法是通过赋予搜索过程一种时变且最终趋于零的概率突跳性，从而可有效避免陷入局部极小并最终趋于全局最优的串行结构的优化算法-Simulated annealing algorithm is the search process by giving a time-change and ultimately tends to zero the probability of jumps, and thus can effectively avoid falling into local min
Simulated-Annealing
- c语言编写的模拟退火算法，可以避免搜索陷入局部最优解，有效解决优化问题。-c language of the simulated annealing algorithm, to avoid the search into a local optimal solution, an effective solution to optimization problems.
monituihuosuanfa
- 模拟退火算法求解TSP问题，Kirkpatric等将热力学中的退火思想引入组合优化领域，提出一种解大规模组合优化问题，特别是NP完全组合优化问题的有效近似算法——模拟退火算法（Simulated annealing algorithm）。-翻译结果（中 > 英）复制结果 Simulated annealing algorithm for solving TSP problems, the Kirkpatric will in thermodynamics of annealing id
SA
- 模拟退火算法 模拟退火算法来源于固体退火原理，将固体加温至充分高，再让其徐徐冷却，加温时，固体内部粒子随温升变为无序状，内能增大，而徐徐冷却时粒子渐趋有序，在每个温度都达到平衡态，最后在常温时达到基态，内能减为最小。根据Metropolis准则，粒子在温度T时趋于平衡的概率为e-ΔE/(kT)，其中E为温度T时的内能，ΔE为其改变量，k为Boltzmann常数。用固体退火模拟组合优化问题，将内能E模拟为目标函数值f，温度T演化成控制参数t，即得到解组合优化问题的模拟退火算法：由初始解i
GSAA
- 模拟退火算法来源于固体退火原理，将固体加温至充分高，再让其徐徐冷却，加温时，固体内部粒子随温升变为无序状，内能增大，而徐徐冷却时粒子渐趋有序，在每个温度都达到平衡态，最后在常温时达到基态，内能减为最小。根据Metropolis准则，粒子在温度T时趋于平衡的概率为e-ΔE/(kT)，其中E为温度T时的内能，ΔE为其改变量，k为Boltzmann常数。用固体退火模拟组合优化问题，将内能E模拟为目标函数值f，温度T演化成控制参数t，即得到解组合优化问题的模拟退火算法：由初始解i和控制参数初值t开始-S
TSP-simulated-annealing-algorithm
- 模拟退火算法是领域随机搜索算法的一种改进——加入概率接受准则，是十分简单的一种智能优化算法，本源码是用于求解TSP问题的模拟退火算法源程序-The simulated annealing algorithm is random search algorithm of field an improved-join probability accept criterion, it is very simple a kind of intelligent optimization algorithm,
PSOBP502
- PSO算法优化BP神经网络，数学建模模拟退火算法的改进-PSO algorithm to optimize the BP neural network, mathematical modeling simulated annealing algorithm improve
10.1.1.87.9872
- 用于函数优化的快速模拟退火算法，非常实用-Fast simulated annealing algorithm for function optimization, very useful
optimizationBook
- 讲述各种优化算法的书籍，如禁忌搜索、遗传算法、模拟退火算法、蚁群算法等-Books about various optimization algorithms such as tabu search, genetic algorithms, simulated annealing, ant colony algorithm
Cpp1
- 模拟退火算法,本算法采用模拟退火算法对TSP问题进行解决，算法优化程度高，运算速度快。-source file of simulated anealing
main0602
- 利用模拟退火算法解决一类组合优化问题—背包问题-Using simulated annealing algorithm to solve a class of combinatorial optimization problem- Knapsack Problem
SSAPSOi
- 模拟退火-粒子群算法，该程序将模拟退火算法和粒子群算法相结合，对优化参数有很好的效果-Simulated annealing- particle swarm optimization algorithm, the program will be the combination of simulated annealing algorithm and particle swarm optimization, optimization parameters have very good result
SA
- 模拟退火算法的讲义，对于初学智能优化算法的人会有很大帮助！-Simulated annealing handouts, intelligent optimization algorithm for the beginner who will be a great help!
matlab
- 燃煤结渣预测，使用支持向量机与模拟退火算法进行优化参数-Slagging Prediction in coal boilers
simuapso
- 一种新的智能优化算法，将粒子群算法与模拟退火算法结合-A new intelligent optimization algorithms, particle swarm algorithm and simulated annealing algorithm
SAPSO
- 0-1背包问题是学习算法时一个非常常用的简单问题，可以用多种智能优化算法实现，这里用到了蚁群算法和模拟退火算法还有两种方法的结合三种方法来实现。-0-1 knapsack problem is a simple learning algorithm is a very common problem, and can use a variety of intelligent optimization algorithm, ant colony algorithm and simulated ann
NNet
- 模拟退火算法对神经网络进行优化并建模。哈哈。-Simulated annealing algorithm to optimize the neural network