百富S80 POS机支付实现

一种大数据机器学习框架的源代码，techstar-ai(The source code of a large data machine learning framework, techstar-ai)

求解0-1规划功能，模仿了LINGO的脚本语言用正则方法处理限制条件和目标函数。(To solve the 0-1 programming function, the scripting language of LINGO is modeled as a regular method to deal with the constraints and target functions.)

说明：  随机生成字符串，中文说明不能少于20字大于20大于20 大于20大于20 大于20大于20 大于20大于20(Tight layout not applied. The left and right margins cannot be made large enough to accommodate all axes decorations.)

Python版本的学生管理系统 管理端账号：000密码：000学生端账号：该生学号密码：1111111、密码均为初始密码，可以随后在系统中自行修改。2、所有操作完成之后必须点退出系统，否则无法保存文件。3、未分配学号的学生无法登陆系统，需先由管理端分配学号之后再登陆系统

熵权法根据各指标的变异程度，利用信息熵计算出各指标的熵权，再通过熵权对各指标的权重进行修正，从而得出较为客观的指标权重。(According to the variation degree of each index, the entropy weight of each index is calculated by using information entropy, and then the weight of each index is revised by the entropy weight, thus objectively obtaining the weight of each index.)

算法思想来自于网上资源，先使用图像边缘和车牌颜色定位车牌，再识别字符。车牌定位在predict方法中，为说明清楚，完成代码和测试后，加了很多注释，请参看源码。车牌字符识别也在predict方法中，请参看源码中的注释，需要说明的是，车牌字符识别使用的算法是opencv的SVM， opencv的SVM使用代码来自于opencv附带的sample，StatModel类和SVM类都是sample中的代码。SVM训练使用的训练样本来自于github上的EasyPR的c++版本。由于训练样本有限，你测试时会发现，车牌字符识别，可能存在误差，尤其是第一个中文字符出现的误差概率较大。(Bits in the predict method, for clarity, add a lot of comments after completing the code and testing, see the source code. License plate character recognition is also included in the predict method. Please refer to the comments in the source code. It needs to be noted that the algorithm used for license plate character recognition is SVM of opencv. The training sample used for SVM training comes from the c++ version of EasyPR on github. Due to limited training samples, you may find errors in license plate character recognition when testing, especially the error probability of the first Chinese character is large.)

说明：  通过各种不同的算法实现室内高精度定位，比如说KNN，随机森林，SVM，等等。(Indoor high-precision positioning is achieved by various algorithms, such as KNN, random forest, SVM, and so on.)

随便下载一篇中文的文本文档，通过这个程序可以将文档进行分词处理，还能够统计词语出现的次数(To download a Chinese text documents, through this program can be word processing document, will also be able to statistics the number of occurrences of words and phrases)

说明：  图像超分辨率技术源码； 基于深度学习的图像超分辨率重建的流程如下[2]： 1.首先找到一组原始图像Image1; 2.将这组图片降低分辨率为一组图像Image2 3.通过各种神经网络结构，将Image2超分辨率重建为Image3(Image3和Image1分辨率一样) 4.通过PSNR等方法比较Image1和Image3，验证超分辨率重建的效果，根据效果调节神经网络中的节点和参数 5.反复执行以上直到第4步的结果比较满意(Image super-resolution technology source code; The process of image super-resolution reconstruction based on deep learning is as follows [2]: 1. First find a set of original images image1; 2. Reduce the resolution of this group of pictures to a group of image2 3. Through various neural network structures, the super-resolution of image2 is reconstructed into image3 (the resolution of image3 is the same as that of image1) 4. Compare image1 and image3 by PSNR and other methods to verify the effect of super-resolution reconstruction, and adjust the nodes and parameters of neural network according to the effect 5. Repeat the above until the result of step 4 is satisfactory)

基于python语言编写的新浪微博爬虫，一天可以抓取1300万条数据。