Тип публикации: статья из журнала
Год издания: 2024
Идентификатор DOI: 10.3390/ijms25073860
Аннотация: <jats:p>This paper offers a thorough investigation of hyperparameter tuning for neural network architectures using datasets encompassing various combinations of Methylene Blue (MB) Reduction by Ascorbic Acid (AA) reactions with different solvents and concentrations. The aim is to predict coefficients of decay plots for MB absorbancПоказать полностьюe, shedding light on the complex dynamics of chemical reactions. Our findings reveal that the optimal model, determined through our investigation, consists of five hidden layers, each with sixteen neurons and employing the Swish activation function. This model yields an NMSE of 0.05, 0.03, and 0.04 for predicting the coefficients A, B, and C, respectively, in the exponential decay equation A + B · e−x/C. These findings contribute to the realm of drug design based on machine learning, providing valuable insights into optimizing chemical reaction predictions.</jats:p>
Журнал: International Journal of Molecular Sciences
Выпуск журнала: Т. 25, № 7
Номера страниц: 3860
ISSN журнала: 16616596
Место издания: Basel
Издатель: Molecular Diversity Preservation International