DE and NLP based QPLS algorithm

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Abstract

As a novel evolutionary computing technique, Differential Evolution (DE) has been considered to be an effective optimization method for complex optimization problems, and achieved many successful applications in engineering. In this paper, a new algorithm of Quadratic Partial Least Squares (QPLS) based on Nonlinear Programming (NLP) is presented. And DE is used to solve the NLP so as to calculate the optimal input weights and the parameters of inner relationship. The simulation results based on the soft measurement of diesel oil solidifying point on a real crude distillation unit demonstrate that the superiority of the proposed algorithm to linear PLS and QPLS which is based on Sequential Quadratic Programming (SQP) in terms of fitting accuracy and computational costs. © Springer-Verlag Berlin Heidelberg 2007.

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Yu, X., Huang, D., Wang, X., & Liu, B. (2007). DE and NLP based QPLS algorithm. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4682 LNAI, pp. 584–592). Springer Verlag. https://doi.org/10.1007/978-3-540-74205-0_63

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