资源列表
3.6lq
- 用RBF网络识别四边形，三角形图像,提取特征量，然后进行仿真识别。-RBF network identification using quadrilateral, the triangle image, extract features, and then simulated to identify.
SimulatedAnnealing
- 模拟退火算法，利用该算法，实现方程的快速求解-Simulated Annealing
myGA
- 用遗传算法求函数 max f(x1,x2) = 100 (x1^2-x2^2)^2 + (1-x1)^2, -2.005 ≤ xi ≤ 2.005 的最大值-Using genetic algorithms get max f (x1, x2) = 100 (x1 ^ 2-x2 ^ 2) ^ 2+ (1-x1) ^ 2, when-2.005 ≤ xi ≤ 2.005
FCM-Overfitting--Subtractive
- 此文件包含三个文件，分别是模糊均值聚类算法，过拟合和减法聚类。-This file contains three documents, namely fuzzy means clustering algorithm, over-fitting and subtraction clustering.
Groundwater-Prediction-on-RFN
- 用径向基网络预测地下水位源代码，给出了不同神经元个数下对应的均方差值以及训练、验证和测试曲线的图形-Radial basis function network forecasting of groundwater source, given the number of different neurons corresponding to the mean square difference and training, validation and test curve graphics
exm_pso_1
- 本matlab代码利用粒子群算法求一个函数的极值-Particle swarm algorithm for a function extremum
bianshi2
- 一个复杂系统神经网络辨识,采用改进BP算法对随机噪声的二阶系统进行模型辨识,效果挺好的.-A complex neural network system identification, using BP algorithm to improve the random noise of the second-order system identification model, the effect of the good.
DE_and_Goal
- 差分进化算法DE，及检验函数Goal。5个检验函数用来验证DE算法的有效性。-Differential evolution algorithm DE, and test function Goal. The five test functions are used to verify the effectiveness of the algorithm of DE.
BPNN.py
- BP全称为Back Propagation，意思为反向传播，该方法是用来对人工神经网络进行优化的，即误差反向传播算法。-BP full name is Propagation Back, mean back propagation, the method is used to optimize the artificial neural network, that is, the error back propagation algorithm.
FLch7NNeg1
- 第七章的用改进的神经网络MBP算法辨识 例7.1 对具有随机噪声的二阶系统的模型辨识，是侯媛彬和汪梅的系统辨识课本上第七章的的实验。 -Chapter VII of the MBP with an improved algorithm for neural network identification Example 7.1 that have random noise second-order system model identification is Houyuan Bin an
TSP
- 蚁群算法是新兴的仿生算法，最初是由意大利学者Dorigo M于1991年首次提出，由于具有较强的鲁棒性，优良的分布式计算机制和易于与其它方法结合等优点，成为人工智能领域的一个研究热点。本程序是实现简单的蚁群算法
fuzzy
- 基于模糊神经网络的源程序，可在此基础上进行修改，matalb-matalb