{'fraction_non_alphanumeric': 0.007832898172323759, 'fraction_numerical': 0.0, 'mean_word_length': 5.612068965517241, '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}}
Validation of Genetic Programming Tool for the Inverse Analysis of Moisture Transport in Building Materials

This paper offers a comparison of two different approaches aimed at the identification of moisture diffusivity of porous building materials as a function of moisture content. The approaches are represented by a traditional deterministic approach using the Boltzmann-Matano method and novel stochastic approach by genetic programming. The results of the comparative analysis show that genetic programming may be used as an alternative to the traditional approaches. On the basis of the very good agreement between experimental data and optimized output of genetic programming, the validation of the genetic programming method may be considered as successful.