• Ravindra Bhardwaj
• Dr GS Sailesh babu
• Dr A.K. Saxena
• Dr Ashok Jangid

Abstract—The use of anaerobic digestion for the energy val- orization of agricultural biomass such as cow dung is thought to be promising. Understanding the operation of biodigesters and controlling their primary operational factors is critical for improving the efficacy of the anaerobic digestion process and increasing biogas generation. This paper shows how the Adaptive Neuro Fuzzy Inference System (ANFIS) model was developed to predict biogas production. The variables from the process were temperature (ºC), pH, Chemical oxygen demand (COD) and Volatile fatty acid (VFA). A database was constructed with the information from the experiments, dividing them into groups of training (70 %) and testing (15%). The experimental results are used to train, test, and verify the ANFIS’ predictions. For the ANFIS model, the determination coefficient, adjusted-R2, and root mean square error are 0.99, 0.9857, and 1.324, respectively. The ANFIS model produced fewer deviations and had a better predictive performance on biogas generation predictions, with satisfactory determination coefficients over 0.99, according to the findings. The experimental and predicted findings are in proximity, indicating that the ANFIS model can be utilized as an alternative method for predicting and improving anaerobic process parameters for obtaining biogas output from cow dung as feedstock. The GA optimization procedure used the ANFIS model as a fitness function. The optimal biogas content was found to be 77 percent, which is greater than the highest number found in the biogas plant’s records, which was 70.1 percent. The operating parameters that produced far more biogas were found to be pH 6.7, COD (mg/L) 64.48, VFA (mg/L) 23.34, and temperature 36.30C.

Biogas, Cow dung, Modeling, Adaptive Neuro- Fuzzy Inference System (ANFIS), Regression and Genetic Algorithm

"Modeling and Optimization of Biogas Generation from Anaerobic Biogas Plant Using ANFIS and Genetic Algorithm", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 3, page no.730-735, March-2019, Available :http://www.jetir.org/papers/JETIR1903N96.pdf

"Modeling and Optimization of Biogas Generation from Anaerobic Biogas Plant Using ANFIS and Genetic Algorithm", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 3, page no. pp730-735, March-2019, Available at : http://www.jetir.org/papers/JETIR1903N96.pdf