In this paper, an accurate algorithm for the method of successive approximations for near-parabolic orbits is established symbolically. Numerical applications are given for motion predictions at fifteen epochs between the years 66 to 1835 for Halley's comet, and at fifteen epochs between the years ...
1. 逐次平均法 【逐次平均法(method of successive averages)】 逐次平均法是一种收敛计算方法求解最大熵费用调和模型的方法,与Frank …sce.hhit.edu.cn|基于2个网页 2. 迭代加权法 docin.com|基于2个网页 例句 释义: 全部,逐次平均法,迭代加权法 更多例句筛选 1. It is based on K-shortest-paths algor...
In numerical analysis, a numerical method is a mathematical tool designed to solve numerical problems. The implementation of a numerical method with an appropriate convergence check in a programming language is called a numerical algorithm cppheat-equationnumerical-methodsgauss-eliminationwave-equationnumeric...
The proposed algorithm based on iterative method applied to solve 2DLFFIE (3.1) is said to be numerically stable with respect to the choice of the first iteration if there exist four independent constants \(k_{1},k_{2},k_{3},k_{4}>0\) such that $$\begin{aligned} D^{*}(u_{m...
The method of successive averages is often used in iterative algorithms for solving various mathematical problems, and travel forecasting models in particular. In each iteration of these algorithms the current solution is averaged with an alternative solution generated by the algorithm. If the problem ...
Jacobi: The Jacobi preconditioner is the diagonal of the matrix A, with an assumption that all diagonal elements are non-zero. SSOR: The symmetric successive over-relaxation preconditioner, implemented as M = (D+L) D^{-1} (D+L)^T. ...
of a walking pedestrian in real time. The active shape model used was generated automatically from real image data and incorporates variability in shape due to orientation as well as object flexibility. A Kalman filter is used to control spatial scale for feature search over successive frames. ...
In view of the shortcomings of existing artificial neural network (ANN) and support vector regression (SVR) in the application of three-dimensional displacement back analysis, Gaussian process regression (GPR) algorithm is introduced to make up for the shortcomings of existing intelligent inversion met...
Due to the local (cellular automata like) structure of the lattice Boltzmann algorithm, the vectorisation and parallelisation is easily possible with a very good performance on modern high performance computers [5]. Another special feature of the lattice Boltzmann method is the efficient and cheap...
Each type of method has its advantages and its challenges. The k-means algorithm, for example, can be applied to very large data sets in which each data point is in Rn for large n, especially if the data are presented to the k-means algorithm in batches, which are subsets of the data...