juliang

说明：  大名鼎鼎的burges 方程的Fortran语言程序。Burges方程式源项为零的NS方程，在某些情况下市很有用的。(Famous burges equation Fortran language program. Burges equation source term to zero NS equations, in some cases, city, very useful.)

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.)

第一个把专家青睐的数学模型技术（NNM 算法模型）引入词汇记忆软件中，并取得了巨大的成功。NNM 算法模型与经典的“艾滨豪斯遗忘曲线”真正的融合于一体，使得该著名的理论在计算机与数学模型下第一次得到了淋漓尽致的发挥。(First a mathematical model of the popular technology expert (NNM algorithm model) the introduction of vocabulary learning software, and has achieved great success. NNM algorithm model and the classic " Ai Bin House forgetting curve" true integration in one, making the well-known theory in computer and mathematical models has been most vividly the first time under play.)

一本介绍fortran语言的不错的书籍，希望你喜欢，版权归属原作者，仅供学习交流(A good book for learning Fortran language, if you read it carefully, you will get what you want.)

密度，比热，热导率，粘性系数随压力、温度变化的UDF(UDF of density, specific heat, thermal conductivity, viscosity coefficient with pressure and temperature.)

含约束的优化问题求解案例，算法简单，求解很方便实用(Constrained optimization problem solving case, the algorithm is simple, easy to solve, practical)

计算改进型SVSLMS算法，在初始收敛速度，时变系统分析能力等方面优于传统的LMS算法(Improved SVSLMS calculation algorithm, the initial convergence rate, time-varying systems analysis capability is superior to the traditional LMS algorithm)

随机数的产生，枚举嵌套算法求解一元多次方程。按批量处理。(The generation of random Numbers, nested enumeration algorithm monadic equation according to the batch processing for many times)

使用奇异值分解来帮助求解最小二乘问题，特别是在方程系数矩阵不满秩的情况下。(SGELSD computes the minimum-norm solution to a real linear least * squares problem: * minimize 2-norm(| b- A*x |) * using the singular value decomposition (SVD) of A. A is an M-by-N * matrix which may be rank-deficient.)

基于Laguerre多项式的拟合程序，可以控制多项式的结束，以及变量alpha。(Based on Laguerre polynomial fitting procedure, you can control the end of polynomials, and variable alpha.)