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code
- Convergence analysis and performance of the extended artificial physics optimization algorithm.artificial physics optimization (EAPO), a population-based, stochastic, evolutionary algorithm (EA) for multidimensional search and optimization. EAP
sapso
- 为了平衡粒子群算法的全局搜索能力和改良局部能力，采用非线性的动态惯性权重即自适应权重法。给出一个用自适应权重的粒子群算法求多元复杂函数的最小值实例。-To balance the PSO global search capability and improved local capacity, the use of non-linear dynamic adaptive inertia weight that the weighting method. Gives an adaptive wei
ANN-F
- 遗传算法优化BP神经网络-非线性函数拟合,将局部寻优与全局寻优相结合-Genetic algorithm to optimize BP neural network- non-linear function fitting, the local optimization combined with global optimization
pso-F
- 粒子群算法的寻优算法-非线性函数极值寻优,将全局寻优与局部寻优结合起来-Particle swarm optimization algorithm- nonlinear function optimization extreme, the global optimization and local optimization combined
jinjisoushuo
- 禁忌搜索是对局部领域搜索的一种扩展，是一种全局逐步寻优算法。搜索过程可以接受劣解，有较强的爬山能力。领域结构对收敛性有很大影响。这个程序的结构简单，为SWAP操作-Tabu Search is an extension of local search field, is a global optimization algorithm gradually. Search process can accept inferior solutions, strong climbing capabilit
mykmeans
- Image Segmentation is vital role in nowadays. The K-means algorithm usually the initial centroids for the K-means clustering are determined randomly so that the determined centroids may reach the nearest local minima, not the global optimum.
dd2kj
- 坐标转换，三维情况下，局部到整体坐标，输入参数为7个-Coordinate conversion, three-dimensional case, the local to global coordinates, the input parameters for the 7
MPPT
- 光伏阵列受到局部阴影遮蔽时其}-v特性会呈现多峰特性，出现多个局部峰值。为了避免传统最大功率点跟踪算法在此情况卜难以找到全局的最大功率点，文章提出了一种优化最大功率点跟踪算法，该算法适用于局部和全局阴影发生的情况、在局部阴影情况卜，通过MATLAB仿真和样机试验与传统最大功率点跟踪算法相比，该优化算法能够判断阴影遮蔽情况是否发生，在局部和全局均一阴影的情况卜都能够跟踪到全局最大功率点避兔光伏阵列的功率损失提高光伏系统效率 -PV array by the partial shadowing
cy
- 模糊控制的一级倒立摆仿真，采用TS模型，TTS模糊模型，是非线形复杂系统模糊建模中一个典型的模糊动态模型。这类模型采用的模糊规则：其前件是依据系统输入、输出间是否存在局部线形关系来进行划分；而其后件是多项式线形方程来表达，从而构成各条规则间的线形组合，使非线形系统的全局输出具有良好的线性描述特性。-Fuzzy Control of an inverted pendulum simulation, using the TS model, TTS fuzzy model, a non-linear
GL-25
- 基于新的交叉算子的全局与局部实数编码遗传算法GL-25-Global and local real-coded genetic algorithms based on parent-centric crossover operators
Immune-particle-swarm-algorithm
- 免疫粒子群算法，这种免疫粒子群优化算法结合了粒子群优化算法具有的全局寻优能力和免疫系统的免疫信息处理机制，并且实现简单，改善了粒子群优化算法摆脱局部极值点的能力。-Immune particle swarm algorithm, this immune particle swarm optimization PSO combines the global optimization ability of the immune system and immune mechanisms of info
ques6
- Write MATLAB code that will do the following. (a) Read a gray image and determine the histogram. (b) Equalize the histogram using normal and adaptive histogram equalization technique (Global). (c) Equalize the histogram using normal and adaptiv
sss
- - Color provide an important clue for extracting the new color LBP histogram features for face recognition using Local Binary Pattern technique. To reduce redundancy RGB color space converted to YCbCr color space. The Local Binary Pattern is a non pa
GA-BP
- GA—BP运用GA对BP神经网络进行训练，取得的最优解作为初始链接权值和阈值，以对BP神经网络局部搜索能力强、全局搜索能力差的缺点进行改进，来达到提高BP神经网络的性能的目的。-GA GA-BP using BP neural network is trained to obtain the optimal solution as the initial link weights and thresholds of BP neural network of local search abilit
Levenberg-Marquardt
- The LMA is a very popular curve-fitting algorithm used in many software applications for solving generic curve-fitting problems. However, as for many fitting algorithms, the LMA finds only a local minimum, which is not necessarily the global minimum.
multi-kernels-SVR
- 全局核（线性）与局部核（高斯）的加权组合，用于改进SVM的拟合和预测能力-The global kernel (linear) and local kernel (Gauss) weighted combination, to improve the SVM ability of fitting and prediction
KMeans
- K-均值聚类算法，属于无监督机器学习算法，发现给定数据集的k个簇的算法。 首先，随机确定k个初始点作为质心，然后将数据集中的每个点分配到一个簇中，为每个点找距其最近的质心， 将其分配给该质心对应的簇，更新每一个簇的质心，直到质心不在变化。 K-均值聚类算法一个优点是k是用户自定义的参数，用户并不知道是否好，与此同时，K-均值算法收敛但是聚类效果差， 由于算法收敛到了局部最小值，而非全局最小值。 K-均值聚类算法的一个变形是二分K-均值聚类算法，该算法首先将所有点作为一个簇，然
PSO
- Rosenbrock函数优化属于无约束函数优化问题，其全局极小值位于一条平滑而狭长的抛物线形状的山谷底部，且为优化算法提供的信息很少，因此找到其全局极小值就显得很困难。根据Rosenbrock函数的这种特性，专门提出了一种改进的PSO算法，该算法引入三角函数因子，利用三角函数具有的周期振荡性，使每个粒子获得较强的振荡性，扩大每个粒子的搜索空间，引导粒子向全局极小值附近靠近，避免算法过早地收敛，陷入局部最优，从而找到Rosenbrock函数的全局极小值。大量实验结果表明，该算法具有很好的优化性能，
NGA
- 小生境遗传算法，该算法易于找出优化问题的所有局部最优解和全局最优解-Niche Genetic Algorithm. The algorithm is easy to find the optimization problem in all local optimal solution and the global optimal solution
hoopoe-heuristic-optimization.txt
- Most optimization problems in real life applications are often highly nonlinear. Local optimization algorithms do not give the desired performance. So, only global optimization algorithms should be used to obtain optimal solutions. This paper propose