ac9cfe_v1004

电池充放电MATLAB模型()

想要acn题库，某天在网上找了很久也没找到，这是我找到的ACM题集，pdf的-Want to acn item bank, one day on the Internet looking for a long time had not found This is what I found ACM question set, pdf" s

stm32f407+usb3300-实现大容量u盘读写(stm32f407+usb3300-Large capacity reader)

划分船舶。用来划分区域做与偶先元分析的东西，可以好好使用(Divide ships. What is used for zoning and dual-priori analysis can be used well.)

说明：  用N来表示训练用例（样本）的个数，M表示特征数目。 输入特征数目m，用于确定决策树上一个节点的决策结果；其中m应远小于M。 从N个训练用例（样本）中以有放回抽样的方式，取样N次，形成一个训练集（即bootstrap取样），并用未抽到的用例（样本）作预测，评估其误差。 对于每一个节点，随机选择m个特征，决策树上每个节点的决定都是基于这些特征确定的。根据这m个特征，计算其最佳的分裂方式。 每棵树都会完整成长而不会剪枝，这有可能在建完一棵正常树状分类器后会被采用）。(N is used to represent the number of training cases (samples), and M is used to represent the number of features. The number of input features m is used to determine the decision result of a node in the decision tree, where m should be far less than m. From N training cases (samples), n times are sampled in the way of put back sampling to form a training set (i.e. bootstrap sampling), and the unselected cases (samples) are used to predict and evaluate the error. For each node, m features are randomly selected, and the decision of each node in the decision tree is determined based on these features. According to these m characteristics, the best splitting mode is calculated. Each tree will grow completely without pruning, which may be adopted after building a normal tree classifier).)

卫星工具包（STK）的英文版说明及中文版教程(Satellite Toolkit (STK) in English and Chinese versions of tutorials that)

说明：  PokemonGo-Bot-master 寶可夢Bot功能(PokemonGo Bot function)

　　用Ｃ语言编写的时间年份程序，只要你输入一个数后，便可以马上看到结果．-C language prepared by the time the year procedures, as long as you enter a number, they can immediately see the result.

说明：  利用IDL进行遥感图像的大气校正，详细说明等(Using IDL for atmospheric correction of remote sensing image, detailed description, etc)

利用Python对各类数据分析算法进行编写，文档包括数据预处理方法，相关的分类和回归分析的算法理论及实践，以及一些实例应用分析。(Use Python to write various data analysis algorithms, including data preprocessing methods, algorithm theory and practice of related classification and regression analysis, and some application analysis.)