Abstract
In this paper, an empirical model based on least square support vector machine (LSSVM) method to predict the output air conditions in a packed tower liquid desiccant dehumidifier is developed. By analysis of the coupled heat and mass transfer between the process air and desiccant solution, six variables are used as the inputs of the LSSVM model, namely: desiccant solution and air flow rates, desiccant solution and air inlet temperature, desiccant concentration, and air relative humidity. Meanwhile, outlet air temperature and relative humidity related with the performance of the dehumidifier are considered as the outputs of the LSSVM model. Compared with the existing theoretical models, the present one is very simple, yet accuracy, and does not need complex theoretical analysis. The experimental results illustrate the effectiveness of the proposed model on performance predicting in a packed tower liquid desiccant dehumidifier. This developed model is expected to have widely applications in performance evaluation, operational monitoring, fault detection and diagnosis.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
