MODELLING AND OPTIMISATION OF ADSORPTION SYSTEM USING STATISTICAL AND MACHINE LEARNING TECHNIQUES FOR WASTE WATER TREATMENT
Abstract
This Research was carried out for the modeling and optimisation of adsorption system using
statistical and machine learning technique for waste water treatment. Waste water treatment data
of Ogunu waste water treatment plant was used for this study. Modeling of the waste water system
was successfully carried out using the Artificial Neural Network Tool of MATLAB Software. The
pH, TSS, Temperature and BOD Value was modeled successfully by Training, Testing and
Validation of the data set. Root mean square error and Correlation coefficient were used to adjudge
the accuracy of the model by checking whether the correlation coefficient is closest to 1 while the
RMSE is closest to zero. Varying the hidden Neurons using 20, 40 and 60 Neurons show that at
60 Neurons the model best fits the experimental data with a correlation coefficient, R of 0.9989599
in comparison with 40 and 20 Neurons whose values are 0.997831 and 0.817057 respectively
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