International Journal of Advance Computational Engineering and Networking (IJACEN)
.
Follow Us On :
current issues
Volume-10,Issue-5  ( May, 2022 )
Past issues
  1. Volume-10,Issue-4  ( Apr, 2022 )
  2. Volume-10,Issue-3  ( Mar, 2022 )
  3. Volume-10,Issue-2  ( Feb, 2022 )
  4. Volume-10,Issue-1  ( Jan, 2022 )
  5. Volume-9,Issue-12  ( Dec, 2021 )
  6. Volume-9,Issue-11  ( Nov, 2021 )
  7. Volume-9,Issue-10  ( Oct, 2021 )
  8. Volume-9,Issue-9  ( Sep, 2021 )
  9. Volume-9,Issue-8  ( Aug, 2021 )
  10. Volume-9,Issue-7  ( Jul, 2021 )

Statistics report
Aug. 2022
Submitted Papers : 80
Accepted Papers : 10
Rejected Papers : 70
Acc. Perc : 12%
Issue Published : 113
Paper Published : 1372
No. of Authors : 3469
  Journal Paper


Paper Title :
Forecasting the Performance of Solar Desalination Plant using Deep Learning Technique

Author :S.Saran Swathi, R.Karthikeyan

Article Citation :S.Saran Swathi ,R.Karthikeyan , (2022 ) " Forecasting the Performance of Solar Desalination Plant using Deep Learning Technique " , International Journal of Advance Computational Engineering and Networking (IJACEN) , pp. 6-9, Volume-10,Issue-1

Abstract : Abstract - The need for desalination plants are increasing in order to overcome the demand for freshwater. Solar desalination, a technique that makes use of solar energy to convert saline water into freshwater, is a booming technique in today’s world. The performance of solar desalination system can be analysed and forecasted using deep learning techniques. The solar desalination system makes use of solar stills which are used to distil the saline water by heating it with solar energy thereby producing freshwater. Hence, the performance of the desalination plant can be forecasted by predicting the solar still’s efficiency. The proposed system makes use of artificial neural network to forecast the performance of tubular solar stills. By predicting the efficiency of solar still, the capital cost involved in building the desalination plant can be reduced. The data from the experimental field is employed here to predict the performance of tubular solar stills. Keywords - Solar Stills, Water Desalination, Deep Learning, Neural Networks

Type : Research paper

Published : Volume-10,Issue-1


DOIONLINE NO - IJACEN-IRAJ-DOIONLINE-18355   View Here

Copyright: © Institute of Research and Journals

| PDF |
Viewed - 21
| Published on 2022-04-15
   
   
IRAJ Other Journals
IJACEN updates
Paper Submission is open now for upcoming Issue.
The Conference World

JOURNAL SUPPORTED BY