Forecasting effluent quality of an industry wastewater treatment plant by evolutionary grey dynamic model

The application of a prediction model is a commendable exercise to evaluate a facility's performance and achieve better quality control in the operation of wastewater treatment plants. This paper proposes a model which integrates grey dynamic modeling and genetic algorithm to predict accurately the effluent quality of an industrial wastewater treatment plant located in southern Taiwan. Model parameters, variables and structures are determined endogenously to minimize errors between observed and predicted values. Modeling feasibility has been proved by using data compared with Monte Carlo simulation and artificial neural network approaches. The results show that the prediction of our proposed model is sensitive to the joint effect of suspended solids and F/M.

[1]  Chia-Yon Chen,et al.  Applications of improved grey prediction model for power demand forecasting , 2003 .

[2]  Deng Ju-Long,et al.  Control problems of grey systems , 1982 .

[3]  Krist V. Gernaey,et al.  Activated sludge wastewater treatment plant modelling and simulation: state of the art , 2004, Environ. Model. Softw..

[4]  Davut Hanbay,et al.  Prediction of wastewater treatment plant performance based on wavelet packet decomposition and neural networks , 2008, Expert Syst. Appl..

[5]  Chao-Hung Wang,et al.  Using genetic algorithms grey theory to forecast high technology industrial output , 2008, Appl. Math. Comput..

[6]  Ni-Bin Chang,et al.  Prediction analysis of solid waste generation based on grey fuzzy dynamic modeling , 2000 .

[7]  Peter A Vanrolleghem,et al.  Parallel hybrid modeling methods for a full-scale cokes wastewater treatment plant. , 2005, Journal of biotechnology.

[8]  Chia-Ming Chang,et al.  The use of grey-based Taguchi methods to determine submerged arc welding process parameters in hardfacing , 2002 .

[9]  Lluís A. Belanche Muñoz,et al.  Prediction of the bulking phenomenon in wastewater treatment plants , 2000, Artif. Intell. Eng..

[10]  Tegoeh Tjahjowidodo,et al.  Identification of pre-sliding and sliding friction dynamics: Grey box and black-box models , 2007 .

[11]  Rong-Song He,et al.  Damage detection by a hybrid real-parameter genetic algorithm under the assistance of grey relation analysis , 2007, Eng. Appl. Artif. Intell..

[12]  Stefano Marsili-Libelli,et al.  Fuzzy prediction of the algal blooms in the Orbetello lagoon , 2004, Environ. Model. Softw..

[13]  Zone-Ching Lin,et al.  Measurement point prediction of flatness geometric tolerance by using grey theory , 2001 .

[14]  Lluís A. Belanche Muñoz,et al.  Towards a model of input-output behaviour os wastewater treatment plants using soft computing techniques , 1999, Environ. Model. Softw..

[15]  Xiping Wang,et al.  Grey prediction with rolling mechanism for electricity demand forecasting of Shanghai , 2007, 2007 IEEE International Conference on Grey Systems and Intelligent Services.

[16]  G. Van Dongen,et al.  Multivariate time series analysis for design and operation of a biological wastewater treatment plant , 1998 .

[17]  B. W. Ang,et al.  A trigonometric grey prediction approach to forecasting electricity demand , 2006 .

[18]  Chaohui Wang,et al.  Predicting tourism demand using fuzzy time series and hybrid grey theory. , 2004 .

[19]  Farouq S Mjalli,et al.  Use of artificial neural network black-box modeling for the prediction of wastewater treatment plants performance. , 2007, Journal of environmental management.

[20]  Diyar Akay,et al.  Grey prediction with rolling mechanism for electricity demand forecasting of Turkey , 2007 .

[21]  Thananchai Leephakpreeda,et al.  Adaptive Occupancy-based Lighting Control via Grey Prediction , 2005 .

[22]  George E. P. Box,et al.  Time series models for forecasting wastewater treatment plant performance , 1996 .

[23]  Robert Tenno,et al.  State and parameter estimation for wastewater treatment processes using a stochastic model , 1995 .

[24]  Sophie Donnet,et al.  Estimation of parameters in incomplete data models defined by dynamical systems , 2007 .

[25]  Bao Rong Chang,et al.  Forecast approach using neural network adaptation to support vector regression grey model and generalized auto-regressive conditional heteroscedasticity , 2008, Expert Syst. Appl..

[26]  Desheng Dash Wu,et al.  Simulation of fuzzy multiattribute models for grey relationships , 2006, Eur. J. Oper. Res..

[27]  M. Mao,et al.  Application of grey model GM(1, 1) to vehicle fatality risk estimation , 2006 .