Paper Title:
Novel New Information Non-Equal-Interval Direct Optimizing Verhulst GM(1,1) Model and its Application to Test Data Processing
  Abstract

The non-equal-interval direct optimum Verhulst GM(1,1) model was built which extended equal interval to non-equal-interval and suited for general data modeling and estimating parameters of direct Verhulst GM(1,1)by optimizing the background value and modified x(n) be taken as initial value. The new model need not pre-process the primitive data, accumulated generating operation (AGO) and inverse accumulated generating operation (IAGO). It was not only suited for equal interval data modeling, but also for non-equal interval data modeling. The new model chooses the modified nth component of X(0) as the starting conditions of the grey differential model. As the new information is fully used, the accuracy of fitting is higher. The example showed that the new model was simple and practical. The new model was worth expanding and applying in test data processing or test on-line monitoring and social science and engineering science.

  Info
Periodical
Key Engineering Materials (Volumes 439-440)
Edited by
Yanwen Wu
Pages
1555-1560
DOI
10.4028/www.scientific.net/KEM.439-440.1555
Citation
Y. X. Luo, W. Y. Xiao, "Novel New Information Non-Equal-Interval Direct Optimizing Verhulst GM(1,1) Model and its Application to Test Data Processing", Key Engineering Materials, Vols. 439-440, pp. 1555-1560, 2010
Online since
June 2010
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Price
$32.00
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