DE and NLP Based QPLS Algorithm

ICIC '07 Proceedings of the 3rd International Conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications. With Aspects of Artificial Intelligence(2007)

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摘要
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.
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关键词
complex optimization problem,differential evolution,qpls,new algorithm,quadratic partial,sequential quadratic programming,proposed algorithm,nonlinear programming,qpls algorithm,de,diesel oil,nlp,computational cost,application.,effective optimization method,application,optimization problem,evolutionary computing
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