A Numerical Integral Algorithm Based on the CAPSO to Improve the Estimation for the Parameters of the Homodyned-K Distribution

2018 ◽  
Author(s):  
Yuqian Wang ◽  
Yufeng Zhang ◽  
Weijia Zhao ◽  
Hongxuan Zhu
Keyword(s):  
Numerical Integral

Stability Analysis Research of Modified CD-Newmark Numerical Integral Method in Seismic Pseudo-Dynamic Test

2014 ◽  
Vol 638-640 ◽  
pp. 1869-1872
Author(s):  
Xin Jiang Cai ◽  
Shi Zhu Tian
Keyword(s):  
Integral Method ◽  
Dynamic Test ◽  
Stable Condition ◽  
Small Time ◽  
Stability Conditions ◽  
Newmark Method ◽  
Time Step ◽  
Unconditionally Stable ◽  
Small Time Step ◽  
Numerical Integral

The characteristics of explicit numerical integral method is without iteration, and the characteristics of inexplicit numerical integral method is unconditionally stable. The traditional CD-Newmark method has the shortcoming of the bigger upper frequency leads to a small time step, a modified combined integral method named MCD-Newmark release the fixed DOF of numerical substructure, then obtained the parameters range of stable condition of experimental substructure, and the unconditionally stable of numerical substructure is also researched,then the strict stability conditions of the traditional CD-Newmark algorithm is resolved. The study provides reference for structural seismic test.

Numerical Integration Combined Gaussian Quadrature with Shuffled Frog Leaping Algorithm in Manufacturing Engineering

2013 ◽  
Vol 722 ◽  
pp. 415-419
Author(s):  
Zhi Zhu Lai ◽  
Dong Mei Ge ◽  
Yun Yan Zhang
Keyword(s):  
Numerical Integration ◽  
Gaussian Quadrature ◽  
Shuffled Frog Leaping Algorithm ◽  
Small Segment ◽  
Precise Result ◽  
Integral Error ◽  
Shuffled Frog Leaping ◽  
Manufacturing Engineering ◽  
Numerical Integral

Several numerical integral error results of Gaussian Quadrature based on subdividing the integral interval arbitrarily is presented, and then an approach for solving numerical integration based on Gaussian Quadrature and Shuffled Frog Leaping Algorithm (SFLA) in Manufacturing Engineering is proposed. SFLA is used to optimize the points in the integral interval in order to get a more precise result with using Gaussian Quadrature in every small segment. Simulation examples of integral validate the algorithm that can compute both singularity functions integral.

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