Optimal operating parameter determination and modeling to enhance methane production from macroalgae

This work aims at proposing a robust strategy to determine the optimal operating parameters based on fuzzy modeling for enhancing productivity of methane using Pelvetia canaliculata. The applied is combination logic (FL) and particle swarm optimizer (PSO). First, FL used build model that describes production experimental datasets. Second, PSO algorithm obtain best-operating conditions process. decision variables in optimization process are beating time feedstock/inoculum ratio (F/I). Each parameter was studied three different values. set 0, 30, 60 min while F/I 0.3, 0.5, 0.7. To assess resulting performance, comparison study carried out between optimized results thought proposed those obtained by Response Surface Methodology (RSM). produced higher accuracy, i.e., lower values Root Mean Squared Errors (RMSEs), compared with RSM. Therefore, confirmed better than