Accuracy Improvement in Sizing Control Valves Using Neural Network
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Abstract
Given the effect of control valves` performance on product quality in various industries, selection of the right size of control valve is critical. Determining the optimal size of control valves depends on some variables whose values are not accurately available and generally approximately are specified using sizing software. The current research proposed a new method for more accurate estimation of control valve variables and enhancing accuracy in valve sizing using neural network. The proposed method depends on neural network capabilities in the approximation of functions and curve fitting. The proposed method was programmed and implemented in the graphical environment of MATLAB graphical user interface (GUI) as the SIZING software and was finally examined using a case study of ISA75.01.01 Standard
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