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Desktop-snow-optimization
- 在电脑桌面下雪，对之前网上的程序进行了修改，用GetDIBits函数代替GetPixel函数并使用桌面穿透技术来解决前一版本不能再win7上运行的问题。-Snow in the computer desktop，online before the procedures were modified, GetDIBits function instead of GetPixel function and use the desktop penetration technology to solve
Reactive-Power-Optimization-matlab
- 程序为改进的遗传算法对配电网无功优化补偿问题。电力系统配电网的无功优化规划是保证配电网安全、经济运行的一项有效手段，是降低网损、提高电压质量的重要措施。-Reactive power optimization is one of the most important control methods to ensure power system operation securely and economically,and an effective measure to improve the v
Genetic-algorithm
- 此段程序是一套完整的设计程序（包括拓扑图、分析表），运用遗传算法优化解决路径规划问题。-The procedures of this section is a complete set of design procedures (including topology, analysis, table), the use of genetic algorithm optimization to solve the path planning problem.
optimization-design-method
- 机械优化设计的一本书，可以帮助初学者很快的学习和认识优化设计这门课。-Golden section method to the optimization design method, can quickly find the objective function of the optimal solution and the most advantages.
immue-algotithm-(1)
- matlab免疫克隆算法目标优化，取得极值，标准型，可修改-Matlab genetic algorithm objective optimization to obtain the extreme value, the standard can be modified
hundunpso
- 针对二维熵图像分割方法在求取最佳阈值时存在计算量大及微粒群算法容易陷 入局部最优且速度较慢等等问题, 提出了基于混沌粒子群优化算法的二维熵图像分割方法。 该方法考虑了图像中像素点灰度 邻域灰度均值对作为阈值对图像进行分割 利用混沌运 动随机性、遍历性和初值敏感性, 将混沌粒子群优化算法与阈值法相结合在二维空间作全局搜 索。实验结果表明了基于混沌粒子群优化算法的二维熵图像分割法用于阈值寻优减少了搜索 时间, 提高了收敛率
Optimization-approach-to--Kalman
- 关于用卡尔曼滤波器优化里程计和陀螺仪的最优方法-On best practices to optimize the odometer and gyroscope using Kalman filter
Optimization-of-workflow-scheduling-in-Utility-Ma
- Grid computing could be the future computing paradigm for enterprise applications, one of its benefits being that it can be used for executing large scale applications. Utility Management Systems execute very large numbers of workflows with very
parameter-optimization-in-GA
- 遗传算法用于多个输入变量的函数参数优化源码，使误差的平方和达到最小- to optimize the source code about Function parameters with multiple input variables in Function parameters with minimum error sum of squares
optimization-design
- 用最优化方法解决最优化问题的技术称为最优化技术，它包含两个方面的内容： (1)建立数学模型，即用数学语言来描述最优化问题。模型中的数学关系式反映了最优化问题所要达到的目标和各种约束条件； (2)数学求解，数学模型建好以后，选择合理的最优化方法进行求解。 -With optimization method to solve the optimization technology, called the optimum technology, it contains two aspect
optimization
- 阻尼算法实现优化，主要是针对线性方程组求解超定方程的一种算法。大家可以试试。-Damping algorithm to realize optimization
trajectory-optimization
- 针对登月舱上升段轨迹优化问题，建立上升舱动力学模型，用无量纲技术建立最优控制模型；以燃料消耗最优为指标，利用Pontrjagin极小值原理，将问题转化为时间自由的两点边值问题(TPBVP)。采用一种基于初值猜测方法和向前扫描法求解TPBVP，得到最优上升轨迹。仿真结果表明：此方法收敛速度快、可靠性高，为月面返回实际应用提供一定的参考。-According to the problem of trajectory optimization for the lunar module in ascen
Full-Stress-Design-of-Optimization
- 《结构优化设计》中的满应力设计VB演示程序，程序中演示的是应力比法，其中含有两个工程实例，例题均在压缩包中的图片中给出了描述。 此为我个人编写的课程演示程序。-Structural optimization design of full stress design VB demo program, presentation program is the stress ratio method, which contains two engineering examples, examples
MMAdapGA
- 遗传算法：用多变异位自适应遗传优化求解一维无约束优化问题-Genetic algorithm: changing ectopic adaptive genetic optimization to solve the one-dimensional unconstrained optimization problem
Constrained-Engineering-Optimization
- 将离散约束优化问题转化为非负整数约束规划问题，开发求解该问题的离散差分进化算法。该算法采用基于混沌映射 的种群初始化、双版本变异和带随机扰动项的取整运算等新策略。针对非线性约束条件，给出惩罚基数的计算方法和连续映 射基函数的表达式，在此基础上设计处理非线性约束的自适应惩罚因子。提出一种刻画种群多样性的新测度——种群二次平 均基因距离及基于新测度的依概率混沌移民算子。将自适应罚函数法、依概率混沌移民操作与离散差分进化算法有机融合， 构造面向工程约束优化的混合离散差分进化算法
Particle-swarm-optimization-(PSO)
- 粒子群优化算法（PSO）应用于神经网络优化程序-Particle swarm optimization (PSO) algorithm is applied to the neural network optimization program
Particle-swarm-algorithm-
- 粒子群算法介绍，帮助了解粒子群算法及MATLAB编程-Particle swarm optimization to help understand the particle swarm algorithm and MATLAB programming
mysql-optimization
- mysql 语法优化 ,提高运行效率的一些技巧-mysql syntax optimization, some techniques to improve the operating efficiency of
CMODE
- 一种改进的微分进化算法用于多目标优化，解决约束优化问题。-An improved differential evolution algorithm for multi-objective optimization to solve constrained optimization problems.
A-GA-based-feature-selection-and-parameters-optim
- Support Vector Machines, one of the new techniques for pattern classifi cation, have been widely used in many application areas. The kernel parameters setting for SVM in a training process impacts on the classifi cation accuracy. Feature