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In this paper, a new fuzzy adaptive local modeling method based on local learning and weighted least squares support vector machine (LS-SVM) is proposed by building fuzzy membership model for the training data. Just as LSSVM, local LS-SVM is also sensitive to outliers or noises. A proper fuzzy membership model based on support vector data description (SVDD) is proposed to deal with the problem. Fuzzy...
Fuzzy model based on support vector machine(SVM-based fuzzy model) was proposed in recent years. Although SVM has an excellent generalization performance, it is considered to have lower computation speed, and a large number of support vectors may be found, which leads to a complex fuzzy model with too many rules. To deal with the problem, the paper presents a new approach called base vector learning(BVL)...
Mooney viscosity is an important while difficult-to-measure quality index with a long-term laboratory assay in nowadays internal rubber mixing processes. In this study, an adaptive kernel learning (AKL) algorithm suitable for nonlinear multi-input-multi-output process modeling is applied to online prediction of Mooney viscosity. The developed AKL algorithm utilizes a sequentially sparse strategy to...
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