June 22, 2024
Abbas Rezaei

Abbas Rezaei

Academic rank: Assistant professor
Education: Ph.D in Electrical engineering
Phone: 083-38305001
Faculty: Faculty ofٍٍ Electrical Engineering


Biodiesel conversion modeling under several conditions using computational intelligence methods
Type Article
Researchers Majid Mohadesi، Abbas Rezaei


he computational intelligence (CI) methods such as artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS) have many applications in chemistry, oil and gas, electronics, financial, telecommunications, and many others. In this article, ANN and ANFIS are used to model and predict the biodiesel conversion under several conditions. The inputs of the proposed CI models are oil type, catalyst type, calcination temperature, catalyst concentration, methanol-to-oil ratio, n-hexane-to-oil volume ratio, reaction time, and reaction temperature and the output is biodiesel conversion. Experimental data of available literature are used to train and test the CI models in MATLAB 7.0.4 software. Comparison between the proposed ANN and ANFIS models and the experimental data show that the proposed CI models are very efficient and fast tools, and there is a good agreement between them and the experimental data with a minimum error. Also, it can be found that the introduced ANN model is more accurate than the ANFIS model. The proposed ANN model has overall MRE% (mean relative error percentage) <1.5%, RMSE (root mean square error) <1.34, R (correlation coefficient) >0.9995, and MAE (mean absolute error) <0.9.