perl文本处理

说明：  考虑了孤岛型微电网的灵活性，在成本最低的条件下，进行优化调度(Considering the flexibility of islanded microgrid, the optimal dispatch is carried out at the lowest cost.)

说明：  [Numerical Methods in Engineering with MATLAB]2005 and midterm exam problems at Ulsan National Institute of Science and Technology

说明：  潮流计算，电力系统分析使用，用于分析潮流，完成各个节点计算(power flow calculation)

关于Python编程的压缩包，包含很多用Python编写的程序。(Python programming on the compressed package, including a lot of procedures written in Python.)

1. 采用BP神经网络设计男女生分类器。采用的特征包括身高、体重、是否喜欢数学、是否喜欢文学、是否喜欢运动共五个特征，BP神经网络包含一个隐层，隐层结点数为5。要求：自行编写代码完成后向传播算法，采用交叉验证的方式实现对于性能指标的评判（包含SE,SP,ACC和AUC，AUC的计算可以基于平台的软件包）。(. using BP neural network to design the classifier for male and female students. The features include height, weight, whether they like mathematics, whether they like literature, and whether they like sports. The BP neural network contains a hidden layer, and the number of hidden nodes is five (5). Requirements: self compiled code, post propagation algorithm, cross validation method to achieve performance evaluation (including SE, SP, ACC and AUC, AUC calculation can be based on platform software package).)

哈夫曼数图形输出,建立,查询,删除,课程设计资料-Huffman few graphics output, the establishment of inquiries, delete, curriculum design information

说明：  采用PSO算法的微电网经济调度优化Economic dispatch optimization of microgrid based on PSO algorithm(Economic dispatch optimization of microgrid based on PSO algorithm)

powerdesigner，很好的书籍，可以帮助学习到如何应用powerdesigner(powerdesigner, good books, can help to learn how to apply powerdesigner)

本书共分5章：第1章介绍GPU通用计算的发展历程，介绍并行计算的历史、现状以及面临的问题；第2章介绍CUDA的使用方法，帮助理解CUDA的编程模型、存储器模型和执行模型，掌握CUDA程序的编写方法；第3章探讨CUDA硬件架构，深入分析Tesla GPU架构与CUDA通用计算的相互作用：第4章总结CUDA的高级优化方法，对任务划分、存储器访问、指令流效率等课题进行探讨；第5章以丰富的实例展示如何使用CUDA的强大性能解决实际问题。(This book is divided into five chapters: Chapter 1 introduces the development process of general-purpose GPU computing, parallel computing introduces the history, current situation and problems Chapter 2 describes the use of CUDA to help understand the CUDA programming model, the memory model and implementation model, master CUDA program writing method Chapter 3 explores CUDA hardware architecture, in-depth analysis of Tesla GPU architecture and CUDA general-purpose computing interactions: Chapter 4 summarizes the CUDA advanced optimization methods, the division of tasks, memory access, instruction stream efficiency and other topics were discussed Chapter 5 with abundant examples show how to use CUDA strong performance to solve practical problems.)

说明：  参数权重分析，灰色关联度分析MATLAB程序(Parameter weight analysis)