[1]XU Lisha,QIAN Xiaoshan,YANG Chunhua.Parameter prediction of multieffect evaporation process combining GM(1,1) with LSSVM[J].CAAI Transactions on Intelligent Systems,2012,7(5):462-466.
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Parameter prediction of multieffect evaporation process combining GM(1,1) with LSSVM

CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume: 7 Number of periods: 2012 5 Page number: 462-466 Column: 学术论文—人工智能基础 Public date: 2012-10-25
Title:
Parameter prediction of multieffect evaporation process combining GM(1,1) with LSSVM
Author(s):
XU Lisha1;  QIAN Xiaoshan2; 3;  YANG Chunhua3
1. Shewai College, Central South University of Forestry and Technology, Changsha 410004, China;
2. Physical Science and Technology College, Yichun University, Yichun 336000, China;
3. School of Information Science & Engineering, Central South University, Changsha 410083, China
Keywords:
wavelet transform;  GM (1;  1) model;  LSSVM model;  multieffect evaporation process;  parameter prediction
CLC:
TP273
DOI:
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Abstract:
A parameter prediction method was proposed for solving the timeseries prediction problem on the parameters of the multieffect evaporation process with high noise and nonstationary, combining GM (1, 1) and least squares support vector machines (LSSVM) based on the wavelet transform model. 〖JP3〗Firstly, the Mallat algorithm was used to decompose and reconstruct the time series of parameters, in order to separate low frequency and highfrequency sequence. Next, the GM (1, 1) model was designed by using a low frequency and highfrequency information sequence based on the LSSVM. Finally, a result of the prediction on all models was analyzed to determine the final prediction results. Production data of a multieffect evaporation process in alumina production were tested in the experiment; and the results show the prediction algorithm is feasible and superior to a single GM (1, 1). The test demonstrated the LSSVM method had a good generalization performance and powerful robustness; and could be used for operation of an optimal evaporation process in the alumina production.
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