搜索资源列表
GA
- 遗传算法（Genetic Algorithm）是一类借鉴生物界的进化规律（适者生存，优胜劣汰遗传机制）演化而来的随机化搜索方法。它是由美国的J.Holland教授1975年首先提出，其主要特点是直接对结构对象进行操作，不存在求导和函数连续性的限定；具有内在的隐并行性和更好的全局寻优能力；采用概率化的寻优方法，能自动获取和指导优化的搜索空间，自适应地调整搜索方向，不需要确定的规则。遗传算法的这些性质，已被人们广泛地应用于组合优化、机器学习、信号处理、自适应控制和人工生命等领域。它是现代有关智能计算
ga
- The genetic algorithm is a method for solving both constrained and unconstrained optimization problems that is based on natural selection, the process that drives biological evolution. The genetic algorithm repeatedly modifies a population of individ
MATLAB-ga
- matlab经典遗传算法GGA求解一元函数优化问题-Matlab genetic algorithm optimization of one element function
GA-MFC
- 这是一个用MFC制作的遗传算法求函数最值的程序，能对算法参数进行更改-This is a MFC produced genetic algorithms function best value program, algorithm parameters can be changed
PSO-GA
- 粒子群算法求解多维约束函数极值，并与遗传算法比较。结果发现，粒子群有很好的精度。-A particle swarm optimization algorithm for solving the extreme value of multi dimensional constrained function, and compared with genetic algorithm. The results show that the particle swarm has a good accurac
ga-m
- matlab遗传算法程序代码，包括主程序及各相关函数文件，注释清晰。目标函数稍作修改即可使用-Genetic algorithm matlab code, including the main program and the relevant function files, clear notes. The objective function can be used to modify slightly
GA
- GA遗传算法，解决了函数优化问题，只要改变目标函数就可以对不同的函数进行优化。-GA genetic algorithm to solve the function optimization problem, just change the objective function can be optimized for different functions.
GA
- 遗传算法的最简单有详细解释的程序，适应度函数fitness可自由更改-The simplest explanation of a detailed program of genetic algorithm, fitness function can be changed freely fitness
ga-SIMPLE
- /求下列元素的最大值：目标函数max=f(x1,x2)=x1*x1+x2*x2 取值范围在{1，2，3，4，5，6，7} //本算法在选择时使用：轮盘赌选择法、交叉时使用：单点交叉。 -A maximum of the following elements: objective function Max = f (x1, x2) x1+ x2 = x1** x2.Scope in,2,3,4,5,6,7 {1}This algorithm is used when the choice
Code-FLC-ANFIS-GA-PSO
- We describe in this paper a new hybrid approach for mathematical function optimization combining Particle Swarm Optimization (PSO) and Genetic Algorithms (GAs) using Fuzzy Logic for parameter adaptation and integrate the results. The new evol
chapter2-GA-MATLAB
- 《MATLAB智能算法30个案例分析》(史峰等)chapter2 基于遗传算法和非线性规划的函数寻优算法- MATLAB intelligent algorithm 30 case studies (History of the peak, etc.) chapter2 function and genetic algorithm based on nonlinear programming optimization algorithm
Nonlinear-DP-and-GA-algorithm
- 非线性规划和ga算法求解函数极值，提高非线性规划的优化能力-Nonlinear programming and GA algorithm to solve the extreme value of function, improve the optimization ability of nonlinear programming
ga
- 关于matlab遗传算法工具箱的应用实例，求解函数最大值，有函数相关详细备注.-On the matlab genetic algorithm toolbox application examples, to solve the maximum function, there are functions related to detailed notes.
GA-BP
- 神经网络遗传算法用于非线性函数的极值寻优matlab代码-Extreme Optimization matlab code of neural network genetic algorithm for nonlinear function
GA-PSO
- 粒子群算法与遗传算法的联合的GA-PSO算法运用，带有测试函数-Joint GA-PSO algorithm using particle swarm optimization and genetic algorithm with test function
GA
- 在matlab中用遗传算法求解函数的最值问题-In matlab using genetic algorithms function best value problems
GA
- 遗传算法求解无约束目标函数，包含选择操作，变异操作，杂交操作，以及将十进制转化为二进制的编码操作-Genetic Algorithm unconstrained objective function comprises selecting operation, mutation, crossover operation, and will be converted to binary coded decimal operation
genetic
- 基于遗传算法和非线性规则的函数寻优算法,结合非线性规划，使算法的收敛速度和求解结果优于基本的遗传算法-GA function optimization algorithm based on rules and nonlinear
Multi-dimensional-function-GA
- 遗传算法处理多维目标函数，约束条件是不同范围下的独立条件。-Genetic algorithm processing multi-dimensional objective function, constraints are independent under the condition of different areas.
GA-add-TO-BP
- matlab神经网络30例的案例3 遗传算法优化BP神经网络-非线性函数拟合-matlab neural network cases 30 cases of 3 genetic algorithm optimization BP neural network- a nonlinear function fitting