Soft-sensing modeling of the carbon content in fly ash based on information fusion for thermal power plant

Abstract

A new algorithm, which is based on information fusion and soft-sensing technique to modeling of the carbon content in fly ash for thermal power plant, is proposed. Firstly, adaptive weighted fusion and least square support vector machine (LSSVM) algorithms are designed. Secondly, for three nonlinear testing functions, BP neural network, LSSVM and LSSVM based on adaptive weighted fusion algorithms are used to modeling respectively. Finally, the algorithms of the LSSVM based on adaptive weighted fusion to modeling of the carbon content in fly ash for power plant are given.