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Process nonlinearity and time-varying behavior of industrial systems are the main factors for poor performance of online soft sensors. To ensure high predictive accuracy, adaptive soft sensor is a common practice. In this paper, an adaptive soft sensor based on moving window Gaussian process regression (GPR) is presented. To make the moving window strategy more efficient, a just-in-time learning (JITL)...
Rainfall prediction is an important part of weather prediction. Compared to conventional methods predicting rainfall rate, the approach applying historical records and data mining technology shows obviously advantage in computing cost. Many excellent works have been done attempting to build predicting model with data mining methods, however, most of them just test the predicting accuracy on data set...
Policy of national student loans accelerates the reform of higher education in China and the process of market mechanism of talents training in a very great degree, and provides the important guarantee for the poor college students. However, at present, high default rate makes commercial bank which provides student loans bear the risk of bad debt, and affects the policy of national student loan to...
In this paper, adaptive-tree-structure-based fuzzy model is applied to predict chaotic time series. The fuzzy partition of input data set is adaptive to the pattern of data distribution to optimize the number of the subsets automatically by binary-tree model. A fuzzy area around every discriminant edge is set up by the membership functions corresponding to every subset of input data. A complex nonlinear...
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