in this research, data fusion (df) method was applied to simulate the hydrological process of taleghan reservoir daily inflow. two different df algorithms were proposed and assessed based on k-nearest neighbors (knn) algorithm. four artificial neural network models and two hammerstein-wiener (hw) models were used as the individual simulation models. comparison of the results between individual ...

This paper presents the development of soft sensor empirical models using support<br /> vector machine (SVM) for continual assessment 2,3-dimethylbutane and 2-methylpentane mole percentage as important product quality indicators in refinery isomerisation process. During model development, critical steps were taken, including selection pre-processing industrial process data, which are broa...

Currently, there are few systematic position control parameter optimization methods for planar switched reluctance motors (PSRMs); how to effectively optimize the parameters of PSRMs is one critical issues that needs be urgently solved. Therefore, a nonlinear dynamic model-based method proposed in this paper. First, improve accuracy motor dynamics model, Hammerstein–Wiener model based on BP neu...

Soft sensors for the on-line estimation of kerosene 95 % distillation end point (D95) in crude distillation unit (CDU) are developed. Experimental data are acquired from the refinery distributed control system (DCS) and include on-line available continuously measured variables and laboratory data which are consistently sampled four times a day. Additional laboratory data of kerosene D95 for the...