Modeling hydrogen production using green algae Chlorella vulgaris utilizing Neural Networks
| Author(s) | : | Gaber Edris, Walid M. Alalayah, Yahia A. Alhamed, A.A. AlZahrani |
| Institution | : | Department of Chemical and MaterialsEngineering College of Engineering, King Abdulaziz University P.O. Box 80204, Jeddah 21589Saudi ArabiaDepartment of Chemical Engineering, Faculty of Engineering, Al |
| Published In | : | Vol. 3, Issue 2 — February 2016 |
| Page No. | : | 162-168 |
| Domain | : | Engineering |
| Type | : | Research Paper |
| ISSN (Online) | : | 2348-4470 |
| ISSN (Print) | : | 2348-6406 |
The production of hydrogen via biophotolysis using algal strain Chlorella vulgaris within an anaerobic batchreactor has been studied.This paper presents the development of a model used to predict the production of hydrogen asfunction of time with Artificial Neural Network (ANN). The model reported is based on a multi-layer perceptron functionneural network (MLP-NN) with a configuration of 3-6-4-1 combined with sigmoid transfer functions tansig,tansig,purline and trainlm respectively. The architecture of the model has been designed in order to mimic the interrelationship between three input parameters: substrate concentration, medium pH and the media contents of nitrogenand phosphate. The ANN model was refined and tested with the use of 48 experiments. The correlation coefficientbetween the experimental data and the model prediction was R2= 0.985 for training and testing. The results showed thatthe ANN model successfully predicted the production of hydrogen from Chlorella vulgarisalgal strain and provided ahigh level of accuracy for the training and testing stages with a maximum error of 6% and 2% respectively.
Gaber Edris, Walid M. Alalayah, Yahia A. Alhamed, A.A. AlZahrani, “Modeling hydrogen production using green algae Chlorella vulgaris utilizing Neural Networks”, International Journal of Advance Engineering and Research Development (IJAERD), Vol. 3, Issue 2, pp. 162-168, February 2016.
