FRIC

C 语言，模拟流体相平衡过程，得到混合气体平衡态以后的工况参数(C language to simulate fluid phase equilibrium process, to obtain a mixed gas equilibrium after working parameters)

非线性算法合集，包括牛顿拉夫逊法，Broyden拟牛顿法，弧长法，割线法。每种算法都包含有线性搜索迭代改进。(Nonlinear algorithm collection, including Newton Raphson, Broyden quasi-Newton method, arc-length method, secant method. Each contains a linear search algorithms for iterative improvement.)

十四节点潮流计算程序，采用了经典的牛拉法潮流计算方法 配以注释(14 nodes trend calculation procedure, using the classic cattle Rafah flow calculation method together with the comments)

频率响应函数计算程序,通过输入结构的响应数据，识别结构的模态参数，matlab(frequency response function，)

运用矩阵摄动法求解结构的复模态参数与动力特性等(Application of Matrix Perturbation Method for Solving Complex Modal Parameters and other dynamic characteristics of the structure)

实现互相关运算 C实现，实现互相关运算 C实现(cross correlation C code implementation)

windows计时器工具，能够精确到毫(0.001)，说明文档请用office2010打开。(windows timer tools, technology is accurate to the mm (0.001), documentation office2010 open.)

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 ). .)

DS证据理论的matlab实现，是数据挖掘的重要理论，可实现故障诊断。(Matlab implementation of DS evidence theory, data mining is an important theory, fault diagnosis can be achieved.)

说明：  最优化课程中的最速下降法matlab程序，利用了wolfe搜索和armijo线搜索(Matlab program of steepest descent method in optimization course, using Wolfe search and Armijo line search)