Implementation of Artificial Neural Network to Forecast Liquid Desiccant Regenerator Performance

Regenerator, an essential part of a liquid desiccant air conditioning system, is capable of efficiently utilizing solar thermal energy. The focus of the investigation lies in assessing the regenerator's performance by studying the regenerator's effectiveness and moisture removal rate. Moreover, an artificial neural network has been modelled to predict the moisture removal rate of the regenerator and outlet air absolute humidity. Results show that the average deviation between the experimental results and predicted values is 0.748% and 4.59% respectively which establishes the reliability of the forecasting model.