FCLS

主流的CFD软件之一 主要用来计算复杂几何形状的流动和换热问题 其数学模型的组成主要是以纳维-斯托克斯方程与各种湍流模型为主体 再加上多相流模型、热辐射模型、化学组分的输运、燃烧与化学反应流模型等. 大多数附加的模型是在主体方程组上补充一些附加源项、附加输运方程与关系式. (One of the major mainstream CFD software used to calculate the complex geometry of the flow and heat transfer mathematical model of the problem are mainly composed of Navier- Stokes equations with various turbulence models as the main coupled multiphase flow model, radiation model, the chemical composition of the transport, combustion and chemical reaction flow model. most of the additional model is on the main equations to add some additional source term, additional transport equation and the relationship.)

一个简单的VC++异常处理例子，通过对选项框的内异常操作，来演示VC++是如何进行处理异常的，对编写出运行完美的VC++程序至关重要。

说明：  关于MATLAB神经网络的案例分析，可以解决预测问题(The case analysis of MATLAB neural network can solve the prediction problem)

说明：  ISO 11898-{1,2,3,4,5}

进化博弈论算法，解决感知网络中联合感知的问题(evolutionary game code)

IdentityServer4_ResourceOwnerPasswords-master

PIC16LF1902-I_SS.pdf

Delphi可视化Ping模拟程序，界面写的粗糙些，主要是用Delphi实现PING命令，代码比较小，点击窗口中的控制按钮可看到Ping的结果。

levy频域辨识模型算法，对系统在已知模型阶次前提下进行模型辨识(levy frequency domain algorithm for identification model)

说明：  聚类分析是数据挖掘中重要的研究内容之一，对聚类准则进行了总结，对五类传统的聚类算法的研究 现状和进展进行了较为全面的总结，就一些新的聚类算法进行了梳理，根据样本归属关系、样本数据预处理、 样本的相似性度量、样本的更新策略、样本的高维性和与其他学科的融合等六个方面对聚类中近 20多个新算 法，如粒度聚类、不确定聚类、量子聚类、核聚类、谱聚类、聚类集成、概念聚类、球壳聚类、仿射聚类、数据流聚 类等，分别进行了详细的概括。(Clustering analysis is one of the important research contents in data mining. The clustering criteria are summarized. The research status and progress of five traditional clustering algorithms are summarized comprehensively. Some new clustering algorithms are used. By combing, according to the sample attribution relationship, sample data preprocessing, sample similarity measure, sample update strategy, sample high-dimensionality and fusion with other disciplines, nearly 20 new algorithms in clustering, Such as granular clustering, uncertain clustering, quantum clustering, nuclear clustering, spectral clustering, clustering integration, concept clustering, spherical shell clustering, affine clustering, data stream clustering, etc., respectively Generalization.)