Paper Title:
Novel New Information Non-Equidistant Optimum GM(1,1) and its Application to Line-Drawing Data Processing in Computer Aided Design
  Abstract

Based on grey system, a new kind of new information non-equidistant optimum grey model GM(1,1) to line-drawing data processing in computer aided design was proposed in which the response function is based on new information x(tn) . The objective function is built to make the fitting mean relative error least and the program was compiled with bacterial foraging algorithm (BFA) combined with particle swarm optimization (PSO) algorithm to optimize the background value and modify the initial value x(tn) of response function. The method of precision inspection was introduced. The programming was authorized with MATLAB7.6 language. Two examples were given, their results were compared with the results based other Grey models, respectively. The method can be used for model establishing on equal interval, as well as on non-interval. Moreover, GM(1,1) model’s fitting precision and prediction is advanced and the scope of application is enlarged. The model is simple and practical, and has a generalizing value in the field of CAD.

  Info
Periodical
Key Engineering Materials (Volumes 439-440)
Edited by
Yanwen Wu
Pages
349-354
DOI
10.4028/www.scientific.net/KEM.439-440.349
Citation
Y. X. Luo, B. Zeng, "Novel New Information Non-Equidistant Optimum GM(1,1) and its Application to Line-Drawing Data Processing in Computer Aided Design", Key Engineering Materials, Vols. 439-440, pp. 349-354, 2010
Online since
June 2010
Export
Price
$32.00
Share

In order to see related information, you need to Login.

In order to see related information, you need to Login.

Authors: Xiao Kun Miao, Ming Yang Li
Abstract:Road traffic accident forecast is a complex stochastic process. Based on the statistics of road traffic accident, Grey Model (1, 1)( short...
551
Authors: De Gang Liao, You Xin Luo
Chapter 1: Material Engineering and its Application
Abstract:The accuracy of the traditional grey model is not high for the monotonic decreasing data. The paper uses the opposite-direction accumulated...
33
Authors: W.Y. Xiao, Y.Y. Luo, Xiao Yi Che
Chapter 1: Advanced Material Technology
Abstract:Monotonically decreasing sequence data for the traditional modeling method using the gray model accuracy is not high , and GM (1, 1) modeling...
81
Authors: You Xin Luo, De Gang Liao, Xiao Yi Che
Chapter 3: Mechanics, Mechatronics and Modeling
Abstract:The accuracy of the traditional grey model is not high for the monotonic decreasing data and the model can not satisfy the compatibility...
284
Authors: Rui Zhou, Jun Jie Li, Yao Chen
Chapter 7: Computational Mechanics
Abstract:This paper starting from the original grey differential equations, through finding the relationship between the raw data and the derivative...
2971