{'fraction_non_alphanumeric': 0.011470281543274244, 'fraction_numerical': 0.0, 'mean_word_length': 6.2727272727272725, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
On the sensitivity analysis for parameter identification of a microalgae dynamical model in sulfur deprived conditions

This study deals with mathematical modeling for predicting Chlamydomonas reinhardtii growth under light attenuation and sulfur deprived conditions leading to hydrogen production in photobioreactor. The strong interactions between biological and physical phenomena require complex mathematical expressions with important number of parameters that have to be identified on the available experimental data. In this paper, a sensitivity function analysis was performed for determining the parameters having the greatest influence on model outputs and proposing a classification of them. Based on this classification, a global identification procedure in tree steps, using data from batch experiments was established. Furthermore, experimental conditions and time periods for data collection (for parameter identification) have been identified.