Application of Factor Analysis in a Large-Scale Industrial Wastewater Treatment Plant Simulation Using Principal Component Analysis-Artificial Neural Network Hybrid Approach

作者：Hasanlou Hamed^*; Abdolabadi Hamid; Aghashahi Mohsen

来源：Environmental Progress & Sustainable Energy, 2015, 34(5): 1322-1331.

• industrial wastewater treatment plant
• modeling
• artificial neural network
• principal component analysis
• factor analysis

The effect operation of industrial wastewater treatment plants is quite complicated due to having diverse qualitative and qicuinhilal n ecu ialion_s in their 41luent characteristics during a day. In this article, we take full advantages of wellknown prediction models to acquire an applicable and constructive operation over industrial treatment plants. It';'-e combine multilayer percept:pun feed fot-uard.neural netwoi-ks with Levenberg Marquardt training !Unction (Trainlm) and princtpal component analysis method to estimate p11, chemical oxygen demand, total dissolved solid; Cl-, turbidity, and achieve appropriate operation of Fajr petrochemical industrial treatment plant for the first time in Dan. Moreover, factor analysis approach was applied to determine the paramount input parameters of the models to reduce the parameters' dimension. Mean square error, root mean square en or. and correlation coefficient (Il() were used for evaluating the performance of the models. Results indicate that correlation reef ficients (10 in the range of 0.8-0.94 showed excellent accuracy of the models in estimating qualitative profile of wastewater Simulation of a whole treatment plant, better prediction of parameters, and proposing ci new hybrid model could be some advantages of this study.

• 出版日期2015-10