首页|Studies from Aristotle University of Thessaloniki in the Area of Machine Learnin g Reported (An Integrated Machine Learning and Metaheuristic Approach for Advanc ed Packed Bed Latent Heat Storage System Design and Optimization)
Studies from Aristotle University of Thessaloniki in the Area of Machine Learnin g Reported (An Integrated Machine Learning and Metaheuristic Approach for Advanc ed Packed Bed Latent Heat Storage System Design and Optimization)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News-A new study on Machine Learning is now available. According to news reporting originating in Thessaloniki, Greece, by NewsRx jour nalists, research stated, "To tackle the challenge of waste heat recovery in the industrial sector, this research presents a novel design and optimization frame work for Packed Bed Latent Heat Storage Systems (PBLHS). This features a Deep Le arning (DL) model, integrated with metaheuristic algorithms." Financial support for this research came from European Commission Joint Research Centre. The news reporters obtained a quote from the research from the Aristotle Univers ity of Thessaloniki, "The DL model was developed to predict PBLHS performance, t rained using data generated from a validated Computational Fluid Dynamics (CFD) model. The model exhibited a high performance with an R(2 )value of 0.975 and a low Mean Absolute Percentage Error (<9.14%). T o enhance the ML model's efficiency and optimized performance, various metaheuri stic algorithms were explored. The Harmony Search algorithm emerged as the most effective through an early screening and underwent further refinement. The optim ized algorithm demonstrated its capability by rapidly producing designs that sho wcased an improvement in total efficiency of up to 85% over availa ble optimized experimental PBLHS designs."
ThessalonikiGreeceEuropeAlgorithmsCyborgsEmerging TechnologiesMachine LearningMetaheuristic AlgorithmAri stotle University of Thessaloniki
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