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gajianonliner
- 遗传算法+非线性寻优，比遗传算法更快更准确-Genetic algorithm (ga)+ nonlinear optimization, faster and more accurate than the genetic algorithm
ABC_Algorithm
- 人工蜂群算法，在多目标非线性优化及路径寻优方面都是很好的算法。-Artificial bee colony algorithm, nonlinear optimization and multi-objective optimization aspects of the path are good algorithms.
ACO_Algorithm
- 蚁群算法的源代码，在路径寻优及多目标非线性优化问题上都有很强的优势。-Ant colony algorithm source code, in the path of multi-objective optimization and nonlinear optimization problem has a strong advantage.
Extremaloptimization
- 神经网络遗传算法函数极值寻优————非线性函数极值寻优-Neural network genetic algorithm optimization function extreme nonlinear function extreme optimization
MATLAB遗传算法
- 遗传算法和非线性规划的函数寻优，BP神经网络优化(Genetic algorithm and nonlinear programming function optimization, BP neural network optimization)
chapter4
- 神经网络遗传算法函数极值寻优——非线性函数极值寻优(Neural network, genetic algorithm, function extreme value optimization nonlinear function extremum seeking)
神经网络遗传算法极值寻优
- 神经网络遗传算法，用于非线性函数的极值寻优，非常好的源码(Neural network genetic algorithm, for nonlinear function extremum seeking, very good source code)
案例4
- 神经网络遗传算法极值函数寻优，对象为非线性函数。(The extremum function of neural network genetic algorithm is optimized, and the object is nonlinear function.)
案例26 粒子群算法的寻优算法-非线性函数极值寻优
- 粒子群算法的寻优算法-非线性函数极值寻优(Optimization algorithm for 26 particle swarm optimization - nonlinear function extremum optimization)
Nonlinear fitting
- 使用拟合残差及残差平方和原理，以人口增长模型为例，结合寻优算法——局部最优解的非线性曲线拟合(Using the principle of fitting residuals and residual sum of squares, this paper takes population growth model as an example, and combines the optimization algorithm, the nonlinear curve fitting of local
基于遗传算法和非线性规划的函数寻优算法
- 用遗传算法进行线性函数以及非线性函数的寻优(The program of solving TSP problem by genetic algorithm)
chapter2
- 基于遗传算法和非线性规划的函数寻优算法;(Function Optimization algorithm based on genetic algorithm and nonlinear programming)
chapter1
- 采用粒子群算法实现多目标的寻优，程序打开即可运行，结果很好。(Particle swarm optimization is applied to achieve multi-objective optimization, and the program is open to run, and the result is very good.)
神经网络遗传算法函数极值寻优-非线性函数极值
- 神经网络遗传算法函数极值寻优-非线性函数极值(Neural network genetic algorithm function extremum optimization - nonlinear function extremum)
PI实现
- 基于改进的PI模型对非线性曲线进行拟合，二次寻优算法进行参数辨识，用逆模型前馈补偿(classical PI modeling)
基于遗传算法优化BP神经网络的非线性预测
- 针对BP神经网络的初始权值和阈值是随机选取的弊端，采用遗传算法寻优BP的初始权值和阈值，然后进行BP训练和测试。遗传算法包括编码 选择 交叉 和变异等操作(Aiming at the disadvantage that the initial weights and thresholds of BP neural network are randomly selected, genetic algorithm is used to optimize the initial weights and
源代码
- 1 基于遗传算法的TSP算法（王辉） 2 基于遗传算法和非线性规划的函数寻优算法（史峰） 3 基于遗传算法的BP神经网络优化算法（王辉） 4 设菲尔德大学的MATLAB遗传算法工具箱（王辉） 5 基于遗传算法的LQR控制优化算法（胡斐）(1 TSP algorithm based on genetic algorithm (Wang Hui) 2 Function optimization algorithm based on genetic algorithm and non
粒子群算法的寻优算法
- 一个关于粒子群算法的非线性函数极值寻优代码(A Nonlinear Function Extremum Code for Particle Swarm Optimization)