The Research of the Water Quality Prediction Model for the Circulating Cooling Water System

Abstract:

Aiming at the common quality faults of scaling and corrosion in circulating cooling water, water quality index were often used to determine the scaling and corrosion of circulating cooling water quality trends. Prediction model of corrosion and scaling rate was built based on BP Neural Network in this paper. The optimal initial individuals were written into the network operating system to optimize the disadvantages of weights and thresholds in BP neural network based on genetic algorithm. The prediction function would output after the network training after comparison of predicted and actual values of the model. The performance of the actual situation was verified to match the model prediction.

• Periodical: Applied Mechanics and Materials (Volumes 385-386)
• Pages: 408-411
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.385-386.408
• Online since: August 2013
• Authors: Qiang Gao, Tian Lu Ma, Jun Fang Li, Chen Guang Li
• Keywords: BP Neural Network (BPNN), Circulating Cooling Water, GA, Water Quality Model

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