cycle-model

Point Gauss Seidel method by fortran. CFD KLAUS A. HOFFMAN

Finding special triples of the form (n, n + 1, n + 2) Write a program that finds all triples of consecutive positive three-digit integers each of which is the sum of two squares, that is, all triples of the form (n, n + 1, n + 2) such that: • n, n+1 and n+2 are integers at least equal to 100 and at most equal to 999 • eachofn,n+1andn+2isoftheforma2+b2.(Finding special triples of the form (n, n+ 1, n+ 2) Write a program that finds all triples of consecutive positive three-digit integers each of which is the sum of two squares, that is, all triples of the form (n, n+ 1, n+ 2) such that: • n, n+1 and n+2 are integers at least equal to 100 and at most equal to 999 • eachofn,n+1andn+2isoftheforma2+b2.)

ANSYS二次开发考虑损伤的材料模型子程序(ANSYS subroutine)

说明：  局部线性回归方法及其稳健形式已经被看作一种有效的非参数光滑方法.与流行的核回归方法相比,它有诸多优点,诸如:较高的渐近效率和较强的适应设计能力.另外,局部线性回归能适应几乎所有的回归设计情形却不需要任何边界修正。(Local linear regression methods and their solid form has been seen as an effective non-parametric smoothing method. Contrary to popular kernel regression methods, it has many advantages, such as: higher efficiency and stronger asymptotic adaptation design capacity. In addition, the local linear regression to adjust to the return of the design of almost all cases does not require any boundary amendment.)

数学中计算曲线积分 数学工具中常用到这样的方法(Calculated curve integral mathematics math tools commonly used in such a way)

纤维状多孔材料的D_B吸声模型，用于计算高孔隙率的刚性多孔材料的吸声系数(D_B absorption model fibrous porous material for sound absorption coefficient high porosity rigid porous material)

说明：  灰色预测模型，对未来数据进行预测，同时还有误差检测(GM(1,1),Grey prediction model, which can forecast future data and detect errors at the same time)

说明：  利用python进行因子分析,因子分析可以进行降维!(Using Python factor analysis, factor analysis can reduce dimensionality!)

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)

This FDTD 2D simulation based on Dennis Sullivan book s. Wave propagation in vacuum background using PML boundary conditions.