Paper Title:
Application of Coupling Model of Projection Pursuit Partial Least-Square Regression Based on Real Coded Accelerating Genetic Algorithm in Land Use Change Forecasting
  Abstract

In study of Land Use Change forecasting, lots of methods have been developed ,such as Markov model、BP algorithm、Canonical correlation analysis, least-squares regression analysis ,but these methods have deficiency in decision and often inadequate in sample size. In response to these deficiencies,projection pursuit Partial Least-Square Regression based on real coded accelerating genetic algorithm model is developed to analyze and predict land use change in Yanji City. The computation results show that the relative error of Coupling Model of Partial Least-Square Regression Based on Projection Pursuit is smaller than traditional Partial Least-Square Regression model’s, and it has improved the prediction precision evidently.

  Info
Periodical
Advanced Materials Research (Volumes 347-353)
Chapter
Chapter 2: Nuclear Energy Engineering
Edited by
Weiguo Pan, Jianxing Ren and Yongguang Li
Pages
1774-1777
DOI
10.4028/www.scientific.net/AMR.347-353.1774
Citation
H. T. Wang, Z. W. Xu, B. Wang, H. Li, "Application of Coupling Model of Projection Pursuit Partial Least-Square Regression Based on Real Coded Accelerating Genetic Algorithm in Land Use Change Forecasting", Advanced Materials Research, Vols. 347-353, pp. 1774-1777, 2012
Online since
October 2011
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: J.H. Shen, Jian Guo Yang
Abstract:This paper presents a partial least squares neural network modeling method for CNC machine tool thermal errors. This method uses the neural...
30
Authors: Xiao Yu Zhang, Hui Yan Zhang
Chapter 1: Mechanic Manufacturing System and Automation
Abstract:The marine corrosion of metal materials is a complex chemical process which is affected by multiple factors that are nonlinear...
237
Authors: Dong Yan, Shao Wei Liu, Jian Tang
Chapter 5: Sensor Technology
Abstract:Feature selection for modeling the high dimensional data, such as the near-infrared spectrum (NIR) is very important. A novel modeling...
1762
Authors: Xiao Qiang Wen, Zhi Ming Xu
Chapter 1: Advanced Material Science and Engineering, Material Processing and Manufacturing Technology
Abstract:A new model was built to predict hydrogen element in coal-fired based on partial least squares regression algorithm, in which there were 4...
275