资源列表
Numerical Approaches to Combustion Modeling
- 关于燃烧数值计算编程的经典书籍，很受欢迎，建议初学者阅读。(The classic books on the combustion flow calculation programming are very popular and are recommended for beginners to read.)
YWFHNPC
- the datestrut and arithmetic with 贪心算法概论()
Combustion Physical and Chemical Fundamental
- 关于数值燃烧学计算编程的经典书籍，很受欢迎，建议初学者阅读。(The classic books on thecombustion flow calculation programming are very popular and are recommended for beginners to read.)
ukawwo
- SVD算法：利用SVD分解的平移,旋转矩阵算法()
111
- 关于有限元计算编程的经典书籍，很受欢迎，建议初学者阅读。(The classic books on finite element programming are very popular and are recommended for beginners to read.)
BP
- bp神经网络进行交通预测的Matlab源代码 数据为1986年到2000年的交通量 ，网络为3输入，1输出 15组数据，其中9组为正常训练数据，3组为变量数据，3组为测试数据(Matlab source code for traffic prediction by BP neural network The data is the traffic volume from 1986 to 2000. The network is 3 input and 1 output. 15 group
hht
- HHT主要内容包含两部分，第一部分为经验模态分解（Empirical Mode Decomposition，简称EMD），它是由Huang提出的；第二部分为Hilbert谱分析（Hilbert Spectrum Analysis，简称HSA）。(The main content of HHT includes two parts. The first part is Empirical Mode Decomposition (EMD), which is proposed by Huang. T
julei
- 聚类算法是给一大堆原始数据，然后通过算法将其中具有相似特征的数据聚为一类。 这里的k-means聚类，是事先给出原始数据所含的类数，然后将含有相似特征的数据聚为一个类中。(The clustering algorithm is given to a large number of original data, and then the data with similar features are gathered into a class by algorithm. The K-mean
SVM
- 训练集：trainset(); 分别取bedroom(1:5,:)和forse(1:5,:)作为训练集； 测试集：testset(); 分别取bedroom(6:10,:)和forse(6:10,:)作为测试集； 标签集：label(); 取bedroom的数据为正类标签为1；forse的数据为负类标签为-1.(Training set: trainset (); take bedroom (1:5,) and forse (1:5,:) as the training set; Tes
xingtailvbo
- 在特殊领域运算形式——结构元素（Sturcture Element），在每个像素位置上与二值图像对应的区域进行特定的逻辑运算。运算结构是输出图像的相应像素。运算效果取决于结构元素大小内容以及逻辑运算性质。(In the special field, the form of computation is Sturcture Element, which performs specific logic operations on every pixel location corresponding
新建文件夹
- 用matlab实现Givens变换，具体说明见m文件(Givens transform matlab code)
spring-boot-spark
- spring boot 和spark嵌套的demo(spring boot join with spark)