Thermal Heat Transfer in Renewable Sources Using Machine Learning Mechanism

Authors

  • S. Sai Kumar Sr Assistant Professor, Department of Information Technology, PVP Siddhartha Institute of Technology, Vijayawada, Andhra Pradesh, India.
  • Bhanu Pratap Pulla Associate Professor, Mechanical Engineer, Alamuri Ratnamala Institute of Engineering & Technology, Shahapur, Asangoan, Mumbai, Maharastra, India
  • R. Sampath Kumar Professor, Department of Aeronautical Engineering, Er. Perumal Manimekalai College of Engineering, Hosur, Krishnagiri, Tamil Nadu, India.
  • A. Sivaramakrishnan Associate Professor, Department of Computer Science and Engineering, Koneru Lakshmaiah Educational Foundation, Green Fields, Vaddeswaram, Guntur, Andhra Pradesh, India.
  • Bharvee Srivastava Assistant Professor, JIBB-Sam Higginbottom University of Agriculture, Technology and Sciences (Deemed to be University), Naini, Prayagraj, India.
  • Prashant Kumar Assistant Professor, Department of Chemical Engineering, Lovely Professional University, Punjab, India

Keywords:

Nanofluids, heat transfer, renewable and sustainable energy, machine learning

Abstract

This paper presents a study on the use of nanofluids to enhance the rate of heat transfer in renewable and sustainable energy systems. Because of the numerous benefits that they provide, engineers who work on the development of thermal systems might discover that ANN are an extremely helpful resource for them. The ANN regression model produced extremely precise and accurate predictions with a high degree of accuracy overall. It was found that the models had an accuracy rate of 97% after using test data that had not been made public in the past. This discovery was made on the premise of the test data. Because they enable the interpretation and forecasting of results, these models are beneficial for engineers and scientists who are conducting experiments to improve heat transfer.

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References

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Published

05.12.2023

How to Cite

Kumar, S. S. ., Pulla, B. P. ., Kumar, R. S. ., Sivaramakrishnan, A., Srivastava, B. ., & Kumar, P. . (2023). Thermal Heat Transfer in Renewable Sources Using Machine Learning Mechanism. International Journal of Intelligent Systems and Applications in Engineering, 12(7s), 36–41. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/4023

Issue

Vol. 12 No. 7s (2024)

Section

Research Article

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