Abstract：Aiming at difficulties in applying pattern recognition optimization method to the process optimization, the concepts of sample weight and class gradient are proposed to improve the existing algorithms according to the feature weight and gradient theory. Simulation results in a nonlinear, multivariable and strongly coupled system illustrate that the proposed method outperforms the conventional pattern recognition optimization method and adaptive optimization method. The proposed method has been applied in the practical online operation condition optimization of an ammonia synthesizer (80,000 tons per year) and the net value of ammonia has raised 0.38% with considerable economic benefit.
阎镜予，沈之宇，薛美盛，孙德敏. 用于过程优化的改进模式识别方法及其应用*[J]. 模式识别与人工智能, 2006, 19(3): 342-348.
YAN JingYu, SHEN ZhiYu, XUE MeiSheng, SUN DeMin. The Improved Pattern Recognition Method for Process Optimization and Application. , 2006, 19(3): 342-348.
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2006, Vol. 19 
