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An update algorithm of least squares support vector machine (LSSVM) is proposed to tackle the time-varying characteristics of the real industrial process. The process variations are concluded to two categories, and accordingly the samples adding and samples replacement are proposed to update the initial LSSVM model incrementally. Then the LSSVM model with proposed updating measures is applied in the...
This paper presents a comparative study on the effects of different data sampling methods to the performance of data-driven models. An engineering benchmark modeling problem is investigated, focused on which, three sampling methods, i.e. orthogonal Latin sampling, uniform design sampling and random sampling are used to generate the training data of different property. Six typical data-driven modeling...
This paper deals with modelling on the nitrogen oxides (NOx) emission of a 600MW coal-fired boiler using artificial neural network (ANN), least squares support vector machine (LSSVM) and partial least squares (PLS) methods based on the experimental data. Some comparisons on the prediction accuracy, time consuming and some other aspects are also given. Two simulation cases are investigated to make...
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