C_classical_src

它是一个计算热通量的c++程序，用udf导入fluent，既可以求解，非常好用的一个，可以作为入门的一个例子学习。(it is a calculated heat flux of c++ program, with udf into fluent, not only can solve, very easy to use one, can be used as a case study entry.)

基于vc++6.0的佳点集遗传算法的编程，里面的各项参数均可由使用者自我调整!(Vc++6.0 based on the good point set genetic algorithm programming, which the parameters can be adjusted by the users themselves!)

music高阶谱分析算法，IDW距离反比加权方法，BP神经网络用于函数拟合与模式识别。( music higher order spectral analysis algorithm, IDW inverse distance weighting method, BP neural network function fitting and pattern recognition.)

经典非线性动力学模型，布鲁塞尔子模型，可直接运行，运算效率高。(nonlinear dynamics Brusselator model)

利用Lax-wendroff两步差分格式求解一维激波管问题Fortran语言(Use a two-step Lax-wendroff Difference Scheme for Solving the one-dimensional shock tube problem Fortran language)

平常练习的一些程序，比较基础，包括求斐波那契数、完数等等(Some of the usual practice procedures, more infrastructure, including seeking Fibonacci numbers, number, etc. End)

说明：  本书用c语言编写了科研和工程中最常用的166个算法,这些算法包括复数 运算、... 4.3.1 【算法23】求一般复矩阵的逆 4.3.2 【算法24】求对称正定矩阵的(good study)

说明：  计算潜在蒸发，方法为彭曼法，需要气温、日照、风速等资料，具体详见程序界面(Pe calculation)

灰色关联度分析是基于灰色系统的灰色过程, 进行因素间时间序列的比较来确定哪些是影响大的主导因素, 是一种动态过程的研究。(Grey Relational Analysis is based on gray gray process, the comparison of the time series between the factors to determine what affect the the big dominant factor, is a dynamic process.)

针对传统的算法如遗传算法、粒子群算法等在TSP问题上求解精确性和求解规模上都还有一定的不足，本文提出了一种基于动态规划思想的粒子群优化算法。该算法用动态规划的方法实现粒子间的信息交互和粒子的进化，并且将粒子群中的粒子按无标度信息指导网络拓扑图的方式进行连接。仿真结果表明该方法能有效地减小误差率，提高解的精确，同时还保持了较低的计算复杂度，具有良好的稳健性。(TSP problem solving for the traditional algorithms such as genetic algorithms, particle swarm optimization accuracy and solving the scale, there is a certain lack of a dynamic programming algorithm-based particle swarm optimization algorithm. The algorithm using dynamic programming method to achieve the evolution of information exchange between the particles and the particles, and particle swarm particle scale-free information guide network topology map to connect. The simulation results show that this method can effectively reduce the error rate and improve the solution precision, while maintaining a low computational complexity, good soundness.)