test_read_file

此源码包是我本学期最优化理论课程的大作业，其中包括了我自己写的以下常用最优化算法的实现代码：最速下降法，牛顿法，非线性最小二乘法，DFP法。fun1，fun2是两个测试函数。谢谢！(This is my source packages optimization theory this semester courses in large operations, including my own to write the following commonly used optimization algorithm code: steepest descent method, Newton method, nonlinear least squares method, DFP method. fun1, fun2 are two test function. Thanks!)

利用pid算法控制电机转速，转速可调，数码管显示，初学者实用(Using PID algorithm to control motor speed, adjustable speed, digital display, beginners practical)

说明：  fluent中udf的实例 计算曳力的例程 可以作为参考以及udf帮助手册(The example of UDF in fluent can be used as a reference to calculate the traction)

概念格的构造问题是形式概念分析应用的前提。由于概念格的时空复杂度随着形式背景的增大而可能指数性的增大，有关概念格的生成问题一直是形式概念分析应用研究的一个重点。国内外的学者和研究人员对此进行了深入的研究，提出了一些有效的算法来生成概念格，这些算法一般可分为两类：批生成算法(Batch Algorithm)和渐进式生成算法(Incremental Algorithm )。。 (Concept lattice structure problem is the premise formal concept analysis applications. Since the concept of space-time lattice with the increasing complexity of the form and context may increase exponentially, generating questions about the concept lattice has been a focus of formal concept analysis applied research. Domestic and foreign scholars and researchers conducted a thorough study made a number of efficient algorithms to generate the concept lattice, these algorithms can be divided into two categories: batch generation algorithm (Batch Algorithm) and progressive generation algorithm (Incremental Algorithm ). .)

说明：  PoleyFitqw曲3线3拟w合类q库 PolewyFitqw曲w线拟w合t类库 PoelywFitq曲w线拟t合类t库 PoelyFtitq曲er线rw合类t库 PolywrFitq曲q线拟wt合t类库(Pwoly33FiwtPoleetPwolyFit555PolywFit)

BESO的python程序，对于进行abaqus的二次开发很有帮助，这样可以将有限元单独在abaqus中进行处理，而优化算法则采用python进行编写(BESO python program, for the secondary development abaqus helpful, so that the finite element can be handled separately in abaqus, while the optimization algorithm is written in python)

工具箱 (粗糙集数据分析工具箱) matla 中使用 (Kit (Rough Set Data Analysis Toolbox))

用來計算帶通濾波器相關參數，可以看出響應圖(Band-pass filter is used to calculate the relevant parameters can be seen in Fig response)

说明：  siPLS和biPLS是两种用于近红外光谱特征波段筛选的变量选择方法，可筛选出与兴关注指标密切相关的特征波段，并去除无关和干扰变量，提高模型稳健性(Bipls and sipls are two variable selection methods for screening the characteristic intervals of near-infrared spectra, which are closely related to performance indicators, to improve the robustness of models.)

最优化课件用于最优化数学方法学习，包括惩罚函数，乘子法等(Optimization courseware for optimizing mathematical methods of learning, including the penalty function multiplier method)