On the exergetic optimization of continuous photobiological hydrogen production using hybrid ANFIS–NSGA-II (adaptive neuro-fuzzy inference system–non-dominated sorting genetic algorithm-II)

摘要: Abstract The aim of this work was to exergetically optimize the performance a continuous photobioreactor for hydrogen production from syngas via water gas shift reaction by Rhodospirillum rubrum . To achieve this, new multi-objective hybrid optimization technique developed coupling elitist NSGA-II (non-dominated sorting genetic algorithm) with ANFIS (adaptive neuro-fuzzy inference system) operational conditions photobioreactor. flow rate and culture agitation speed were independent variables, while rational process exergy efficiencies as well normalized destruction dependent variables. used establish an objective function each variable individually based on model then utilized approach find optimal operating simultaneously leading highest lowest destruction. Consequently, best extracted using Pareto front set consisting seven optimum points. Accordingly, 13.34 mL/min 383.33 rpm yielding efficiency 21.66%, 85.64%, 1.55 found conditions.