Modelling Treatment by Adsorption from Waste Water Using Artificial Neural Network and Multiple Linear Regressions (MLR) Approaches | Chapter 8 | Chemical and Materials Sciences: Developments and Innovations Vol. 5

 

Artificial neural networks (MLP-ANN) and multiple linear regressions (MLR) models were used for predicting the dynamic adsorption of the complex system of adsorbent adsorbate in the solid-liquid phase. A structure of 09 neurons in the input layer, 16 neurons in the hidden layer, and 1 neuron in the output layer was built.

 

According to the statistically obtained result for the ANN model in terms of root mean square error (RMSE= 0.0521) and correlation coefficient (R = 0.991), the ANN presents a powerful tool and gives more significant results than the MLR model.

 

 

Author(s) Details

Meriem. Sediri
Biomaterials and Transport Phenomena Laboratory (LBMPT), University of Médéa, Ain D’Heb 26000, Médéa, Algeria.

 

Salah. Hanini
Biomaterials and Transport Phenomena Laboratory (LBMPT), University of Médéa, Ain D’Heb 26000, Médéa, Algeria.

 

Maamar. Laidi
Biomaterials and Transport Phenomena Laboratory (LBMPT), University of Médéa, Ain D’Heb 26000, Médéa, Algeria.

 

Siham. Abbas Turki
Department of Electrics and Computing Engineering, University of Médéa, Ain D’Heb 26000, Médéa, Algeria.

 

 

Hakima. Cherifi
Biomaterials and Transport Phenomena Laboratory (LBMPT), University of Médéa, Ain D’Heb 26000, Médéa, Algeria.

 

Hamadache. Mabrouk
Biomaterials and Transport Phenomena Laboratory (LBMPT), University of Médéa, Ain D’Heb 26000, Médéa, Algeria.

 

Please see the book here:- https://doi.org/10.9734/bpi/cmsdi/v5/1932