zuixin

假设有一个能装入总体积为T的背包和n件体积分别为w1 , w2 , … , wn 的物品，能否从n件物品中挑选若干件恰好装满背包，即使w1 +w2 + … + wn=T，要求找出所有满足上述条件的解。例如：当T=10，各件物品的体积{1，8，4，3，5，2}时，可找到下列4组解：（1，4，3，2），（1，4，5），（8，2），（3，5，2）。 [需求分析](Suppose there are a load of the backpack of the total volume of T and n volumes were w1, w2, ... wn items, whether selected from n items a number of exactly filled backpack, even if w1+w2+ ...+ wn = T, find out the solution of all the above conditions are met. For example: when T = 10, the volume of items {1,8,4,3,5,2}, can be found in the following four solutions: (1,4,3,2), (1,4,5 ), (8,2), (3,5,2). [Needs Analysis])

说明：  共轭梯度法（Conjugate Gradient）是介于最速下降法与牛顿法之间的一个方法，它仅需利用一阶导数信息，但克服了最速下降法收敛慢的缺点，又避免了牛顿法需要存储和计算Hesse矩阵并求逆的缺点，共轭梯度法不仅是解决大型线性方程组最有用的方法之一，也是解大型非线性最优化最有效的算法之一。 在各种优化算法中，共轭梯度法是非常重要的一种。其优点是所需存储量小，具有步收敛性，稳定性高，而且不需要任何外来参数。(Conjugate gradient method Gradient) is a method between the steepest descent method and Newton's method. It only uses the first derivative information, but overcomes the disadvantage of slow convergence of steepest descent method, and avoids the disadvantage of storing and calculating Hesse matrix and solving inverse of Newton's method. Conjugate gradient method is not only one of the most useful methods to solve large-scale linear equations, but also the most effective method to solve large-scale nonlinear optimization One of the algorithms of. Among all kinds of optimization algorithms, conjugate gradient method is very important. It has the advantages of small storage, step convergence, high stability and no external parameters.)

通过FORTRAN编写damage子程序，在板材成形中实现破裂的可视化及成形极限预测(FORTRAN subroutine written by damage to achieve rupture of visualization in sheet metal forming and forming limit prediction)

用ABAQUS及其子程序解决热冲压热力耦合问题(Subroutine with ABAQUS and hot stamping coupled thermal problem solving)

矩阵转换问题 行与列的个数均为n 的矩阵称为n 阶方阵。假定矩阵中的每个元素的值在0到9之间，则可以将矩阵中的所有元素按行依次排列得到一个“单行矩阵字符串”。(Matrix conversion, the number of rows and columns of the matrix n are called n-order square. Assume that each element of matrix value in the 0 to 9, you can press all the elements of the matrix rows in order of priority for a " single matrix string." )

关于多智能体系统一致性的程序，解微分方程(Consistency of multi-agent systems program)

实现位场数据的向上延拓运算，有效的消除数据中的噪音及浅部干扰。(Realize the potential field data upward continuation operator, effectively eliminate the noise in the data and shallow interference.)

说明：  LMF方法解非线性方程组，有例子，可以直接运行！(LMF method to solve nonlinear equations, there are examples, can be directly run!)

弗洛伊德算法最短距离的实现，输入为邻接矩阵，输出为最短距离矩阵。(Freud' s realization of the algorithm for the shortest distance, enter the adjacency matrix output for the shortest distance matrix.)

fractal compression using wavelet