Adaptive Network Fuzzy Inference System and Particle Swarm Optimization of Biohydrogen Production Process

Green hydrogen is considered to be one of the best candidates for fossil fuels in near future. Bio-hydrogen production from dark fermentation organic materials, including wastes, most cost-effective and promising methods production. One main challenges posed by this method low rate. Therefore, optimizing operating parameters, such as initial pH value, temperature, N/C ratio, concentration (xylose), plays a significant role determining The experimental optimization parameters complex, expensive, lengthy. present research used an data asset, adaptive network fuzzy inference system (ANFIS) modeling, particle swarm model optimize coupling between ANFIS PSO demonstrated robust effect, which was evident through improvement based on four input parameters. results were compared with RSM models. proposed increase biohydrogen 100 mL/L 200 obtained using ANOVA.