风场仿真

《MATLAB 程序设计与实例应用》，一本matlab编程的书籍，比较适合于初学者学习( MATLAB Program Design and examples of application, a matlab programming books, suitable for beginners to learn)

这个程序是对系数矩阵进行乔列斯基分解，并对线性方程组求解的通用程序(This program is the coefficient matrix Qiaoliesiji decomposition, solving linear equations and general program)

该源码可用于分析气候多因子的主分量分析，有几个不同的源码例子，可进行比较(The source code can be used to analyze the climate more than the principal component factor analysis, has several different source code examples, can be compared)

经典异步电机直接转矩控制，的simulink仿真(Classic direct torque control induction motor, the simulink simulation )

用于利用中国余数定理进行被除数恢复中几个函数的设计编写。(Using the Chinese remainder theorem is used for several functions dividend restoration design preparation.)

说明：  基于CRAFT的多阶段柔性设备布局优化算法 　　多阶段设备布局下的总成本包括设备拆装成本、物料搬运成本以及区域利用成本,问题的目标是最小化总成本。首先,在分析问题的基础上,建立基于多阶段设备布局优化目标的数学模型 其次,采用改进的CRAFT启发式算法优化单阶段设备布局 进一步,提出基于单阶段设备布局算法的多阶段启发式算法,优化多阶段设备布局 最后,数值实验表明算法优化后总成本降幅达28.57％. (CRAFT-based multi-stage flexible equipment layout optimization algorithm under the multi-stage equipment, the layout of the total cost including equipment disassembly cost, material handling costs as well as regional use of cost, the goal is to minimize the total cost. First of all, the analysis of the problem on the basis of the equipment based on the layout of multi-stage mathematical model of optimization objectives Secondly, the adoption of improved CRAFT heuristic algorithm to optimize the layout of single-stage device to further, based on equipment layout algorithm for single-stage multi-stage heuristic algorithm, optimize the layout of multi-stage equipment Finally, numerical experiments show that the optimized algorithm for the total cost of 28.57 percent decrease.)

说明：  用其中一半的数据采用ANN-BP算法设计分类器，另一半数据用于测试分类器性能。(Half of the data used by ANN-BP algorithm design classifier, the other half of the data used to test the classifier performance.)

分支界限法求解整数规划，matlab 分支界限法求解整数规划，matlab(branch and cut with matlab )

algo pour la compression JPEG des images

NOAA网站AVHRR卫星数据绘图（SST）。数据选用原因:它本身是已经被处理过的27年（1982-2008）全球月平均数据，而且数据精度非常高，对于研究全球SST的气候态特征有较好的说服性；另外，选择2月与8月的数据，对描述海洋水温的平面分布更具有代表性。 (NOAA AVHRR satellite data mapping site (SST). Data Selection reasons: it is itself already been treated for 27 years (1982-2008) global average monthly data, and the data accuracy is very high, for the study of global climate SST state characteristics have better persuasive addition, February with the data in August, and the description of ocean water temperature plane distribution more representative.)