Thermal Heat Transfer in Renewable Sources Using Machine Learning Mechanism
Keywords:
Nanofluids, heat transfer, renewable and sustainable energy, machine learningAbstract
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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