Comparative study on prediction of fuel cell performance using machine learning approaches Lei Mao Lisa Jackson 2134/22492 https://repository.lboro.ac.uk/articles/journal_contribution/Comparative_study_on_prediction_of_fuel_cell_performance_using_machine_learning_approaches/9222638 This paper provides a comparative study to evaluate the effectiveness of machine learning techniques in predicting fuel cell performance. Several methods applied in fuel cell prognostics are selected, including a neural network, an adaptive neuro-fuzzy inference system, and a particle filtering approach. Test data from a fuel cell system is used for the evaluation. From the results, the advantages and disadvantages of these approaches are compared, which can provide a general framework for the selection of the necessary algorithms for fuel cell prognostics under different conditions. 2016-09-19 12:22:44 Fuel cell Prognostics Machine learning technique Neural network Adaptive neuro-fuzzy inference system Particle filtering approach Engineering not elsewhere classified