092059256reinforcement_by_sutton

说明：  root music 算法估计精度更加优秀(root music The estimation accuracy of the algorithm is better)

In order to minimize power losses caused by high current and improve the voltage profile in the network distribution, the introduction of dispersed generations also called productions decentralized in distribution network (DG) plays an important role. The installation of DGs directly affects the power requested or purchased

计算滑动轴承滑动效率和受的摩擦力，并绘制出曲线(Calculation of efficiency and by the sliding bearing sliding friction, and draw out the curves)

说明：  SVM四分法代码，用matlab编写的，可以很好地运行。(SVM criss and cross code, written in matlab, you can run well.)

simulates the motion of a pendulum in 3-D usin RK-4.

This code is to find standard deviation of wind speed data

ofdm基本功能,可以展示ofdm的基本功能图形并茂。(that is a foundamental techology)

dpsk modulator digtal system radio

一款RS缩短码的源代码，可修改其中主程序的数据变任意一种RS码的编码器，此程序经多次验证均正确，且采用标准代码格式描写，易读。(A shortened RS code source code, which can modify data in the main program code change any of the RS encoder, this procedure has been repeatedly verified are correct, and the use of standard code format description, easy to read.)

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.)