anneal_SimulatedAnnealing

Free Convection Past a Vertical Flat Plate

图论相关的算法和应用，是自己数学建模时收集和自己开发的一些程序，值得你学习！(Graph-related algorithms and applications, mathematical modeling their own collection and some of their own development process, it is worth you learn!)

THE FILE USE FOR ANIMATE THE DATA PLOT

对ＬＥＡＣＨ协议在ＭＡＴＬＡＢ里面仿真，以及改进的ＬＥＡＣＨ协议在ＭＡＴＬＡＢ里面仿真，之后对比(Simulation of LEACH protocol in MATLAB)

说明：  为考查各种不确定性因素对系统运行的影响，需要大量地重复性潮流计算。结合概率理论形成的概率潮流计算能够充分考虑这些不确定性因素。由概率潮流计算可以得到节点电压、电流、支路潮流的均值、方差、概率密度函数等统计特性，从而更全面地反映系统运行状况。(In order to examine the impact of various uncertainties on system operation, a large number of repetitive power flow calculations are needed. The probabilistic power flow calculation based on probability theory can fully consider these uncertainties. Statistical characteristics of node voltage, current and branch power flow, such as mean, variance and probability density function, can be obtained from the calculation of probabilistic power flow, thus reflecting the operation status of the system more comprehensively.)

一个近似熵的源代码，一个熵代码，主要运行环境：matlab.第一个主要用与生物信号的检测,主要用于生物医疗工程的信号处理方面。（由matlab高手编）(An approximate entropy of the source code, an entropy code, the main operating environment: matlab. The first major use with the bio-signal detection, mainly for biomedical signal processing aspects of the project. (From matlab master ed.))

This article presents a new adaptive framework for locally parallel texture modeling.

测试可以跑，根据自己情况修改下函数即可. NSGA-III 首先定义一组参考点。然后随机生成含有 N 个（原文献说最好与参考点个数相同）个体的初始种群，其中 N 是种群大小。接下来，算法进行迭代直至终止条件满足。在第 t 代，算法在当前种群 Pt的基础上，通过随机选择，模拟两点交叉（Simulated Binary Crossover，SBX）和多项式变异 产生子代种群 Qt。Pt和 Qt的大小均为 N。因此，两个种群 Pt和 Qt合并会形成种群大小为 2N 的新的种群 Rt=Pt∪Qt。 为了从种群 Rt中选择最好的 N 个解进入下一代，首先利用基于Pareto支配的非支配排序将 Rt分为若干不同的非支配层（F1，F2等等）。然后，算法构建一个新的种群St，构建方法是从 F1开始，逐次将各非支配层的解加入到 St，直至 St的大小等于 N，或首次大于 N。假设最后可以接受的非支配层是 L层，那么在 L+ 1 层以及之后的那些解就被丢弃掉了，且 St FL中的解已经确定被选择作为 Pt+1中的解。Pt+1中余下的个体需要从 FL中选取，选择的依据是要使种群在目标空间中具有理想的多样性。(The test can run and modify the function according to its own situation. NSGA-III first defines a set of reference points. Then the initial population containing N individuals (preferably the same number of reference points as the original literature) was randomly generated, where N was the size of the population. Next, the algorithm is iterated until the termination condition is satisfied. On the basis of current population Pt, the algorithm simulates two-point crossover (SBX) and polynomial mutation to produce offspring population Qt by random selection.)

CTP protocol DOC for WSN

刘宝碇《不确定规划及应用》第4章例4.2的matlab程序,58页。内容简单，但可以有效的帮助初学者理解随机模拟的原理。(Liu anchor " uncertain Planning and Applications" in Chapter 4 Example 4.2 matlab program, 58. Content is simple, but can effectively help beginners understand the principles of stochastic simulation.)