python 读写

说明：  CN对图像进行像素级的分类，从而解决了语义级别的图像分割（semantic segmentation）问题。与经典的CNN在卷积层之后使用全连接层得到固定长度的特征向量进行分类（全联接层＋softmax输出）不同，FCN可以接受任意尺寸的输入图像，采用反卷积层对最后一个卷积层的feature map进行上采样, 使它恢复到输入图像相同的尺寸，从而可以对每个像素都产生了一个预测, 同时保留了原始输入图像中的空间信息, 最后在上采样的特征图上进行逐像素分类。(CN classifies images at the pixel level, thus resolving the problem of semantic segmentation at the semantic level. Unlike classical CNN, which uses full-connection layer to get fixed-length feature vectors after convolution layer for classification (full-connection layer + soft Max output), FCN can accept any size of input image, and uses deconvolution layer to sample feature map of the last convolution layer to restore it to the same size of input image, so that each pixel can be generated. At the same time, the spatial information of the original input image is retained. Finally, the pixel-by-pixel classification is carried out on the feature map sampled above.)

用于abaqus软件的单元删除，是应用在abaqus软件后处理时，删除已经失效的单元(Unit for abaqus software delete application abaqus software processing, the unit has failed to delete)

machine learning 方面有关于Bayesian Review and Gaussian Processes的资料，语言是python(machine learning aspects of information concerning the Bayesian Review and Gaussian Processes, language is python)

说明：  支持向量机回归预测，包括模型的建立和保存(Support vector machine regression prediction, including the establishment and preservation of the model)

SVR源码以及详细交通流预测模型，里面有SVM，SVR，LSSVM(SVR source code and detailed traffic flow prediction model, including SVM, SVR, LSSVM)

说明：  边缘检测的Robert算子Python实现，一个是带噪声，一个是不带噪声的代码(Implementation of Edge Detection)

说明：  用于批量提取abaqus的节点力，而不是积分点的力(Node force for batch extraction of abaqus, not integral point force)

说明：  采用GA、ACO分别对ANFIS和SVM进行优化，预测股市的数据(Using GA and ACO to optimize ANFIS and SVM respectively to predict the data of stock market)

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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.)