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Please use this identifier to cite or link to this item: http://repository.iitr.ac.in/handle/123456789/10991
Title: Application of artificial neural network for predicting performance of solid desiccant cooling systems – A review
Authors: Jani D.B.
Mishra, Manish
Sahoo, Pradeep K.
Published in: Renewable and Sustainable Energy Reviews
Abstract: In present study, an attempt has been made to review the applications of artificial neural network (ANN) for predicting the performance of solid desiccant cooling systems. Different types of neural networks are applied to model the solid desiccant cooling systems. With use of experimental data, an ANN model was developed which is based on different algorithms. Available experimental data were divided into two categories for training and testing of the ANN model. Later on, trained ANN model was tested for predicting the performance of system based on various input and output parameters such as air stream flow rates, temperatures and humidity ratios, pressure drop, dehumidifier effectiveness, cooling capacity, regeneration temperature, power input, coefficient of performance etc. So, present review proposes the use of ANN based model to simulate the relationship between inlet and outlet parameters of the system. The ANN predictions for these parameters usually agreed with the experimental values with higher correlation co-efficient. The previous studies show that ANNs can be used with a higher precision in guessing the performance of solid desiccant cooling systems. This review is useful for making opportunities to further research of ANNs and its feasibility which is becoming common in the coming days. © 2017 Elsevier Ltd
Citation: Renewable and Sustainable Energy Reviews (2017), 80(): 352-366
URI: https://doi.org/10.1016/j.rser.2017.05.169
http://repository.iitr.ac.in/handle/123456789/10991
Issue Date: 2017
Publisher: Elsevier Ltd
Keywords: ANN
COP
Dehumidifier
Desiccant cooling
Regeneration
ISSN: 13640321
Author Scopus IDs: 57077089900
55126794600
22835953900
Author Affiliations: Jani, D.B., Department Gujarat Technological University, GTU, Ahmedabad, India
Mishra, M., Department of Mechanical & Industrial Engineering, Indian Institute of Technology Roorkee247667, India
Sahoo, P.K., Department of Mechanical & Industrial Engineering, Indian Institute of Technology Roorkee247667, India
Corresponding Author: Jani, D.B.; Department Gujarat Technological University, GTUIndia; email: dbjani@rediffmail.com
Appears in Collections:Journal Publications [ME]

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