Advances in Engineering Software
Application of RBF Network Based on Immune Algorithm to Predicting of Wastewater Treatment
ISNN 2009 Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part III
Pathological infant cry analysis using wavelet packet transform and probabilistic neural network
Expert Systems with Applications: An International Journal
Hi-index | 12.05 |
In this paper, an intelligent wastewater treatment plant model is developed to predict the performance of a wastewater treatment plant (WWTP). The developed model is based on wavelet packet decomposition, entropy and neural network. The data used in this work were obtained from a WWTP in Malatya, Turkey. Daily records of these WWTP parameters over a year were obtained from the plant laboratory. Wavelet packet decomposition was used to reduce the input vectors dimensions of intelligent model. The suitable architecture of the neural network model is determined after several trial and error steps. Total suspended solid is one of the measures of overall plant performance so the developed model is used to predict the total suspended solid concentration in plant effluent. According to test results, the developed model performance is at desirable level. This model is an efficient and a robust tool to predict WWTP performance.