Optimizing Pyramid Solar Still Performance using Response Surface Methodology and Artificial Neural Networks
Last updated: 28 Dec 2024
10.21608/jesj.2024.296455.1079
pyramid solar still, Response surface methodology, Feed forward Artificial Neural Network, Thermal Efficiency, water yield
Godwin
Immanuel
Sathyabama Institute of Science and Technology
godwinimmanuel@yahoo.com
Chennai
Samson
Isaac
Department of Biomedical Engineering, Karunya Institute of Technology and Sciences, Coimbatore, Tamil Nadu 641114, India.
isaacsamson@gmail.com
Coimbatore
Amanpreet
Kaur
Department of Computer Science & Engineering, Chitkara Institute of Engineering and Technology, Chitkara University, Rajpura, Punjab 140401, India.
amanpreet.cse@gmail.com
Rajpura
Pearlin
E
Department of English, Panimalar Engineering College, Chennai 600123, Tamil Nadu, India.
dr.pearlin@gmail.com
Chennai
Shailendra
Bohidar
Kumar
Department of Mechanical Engineering, School of Engineering & I.T.,MATS University , Raipur,
shailendrakumarbohi@gmail.com
Raipur
Raja
Manikandan
Department of Electronics and Communication Engineering, K.Ramakrishnan College of Technology, Trichy, Tamil Nadu 621112, India.
raja.ect@gmail.com
Trichy
36
1
51808
2024-12-01
2024-06-09
2024-12-01
40
50
2314-5579
2682-3942
https://jesj.journals.ekb.eg/article_396404.html
https://jesj.journals.ekb.eg/service?article_code=396404
396,404
High quality original papers
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Journal of Environmental Studies
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Optimizing Pyramid Solar Still Performance using Response Surface Methodology and Artificial Neural Networks
Details
Type
Article
Created At
28 Dec 2024