Mr Direnc Pekaslan's Outputs (2)

Machine Learning Pipeline for Energy and Environmental Prediction in Cold Storage Facilities (2024)
Journal Article
Alkhulaifi, N., Bowler, A. L., Pekaslan, D., Serdaroglu, G., Closs, S., Watson, N. J., & Triguero, I. (2024). Machine Learning Pipeline for Energy and Environmental Prediction in Cold Storage Facilities. IEEE Access, 12, 153935-153951. https://doi.org/10.1109/access.2024.3482572

As energy demands and costs rise, enhancing energy efficiency in Food and Drink Cold Storage (FDCS) rooms is important for reducing expenses and achieving environmental sustainability ambitions. Forecasting electricity use in FDCSs can help optimise... Read More about Machine Learning Pipeline for Energy and Environmental Prediction in Cold Storage Facilities.

Predictability of higher heating value of biomass feedstocks via proximate and ultimate analyses – A comprehensive study of artificial neural network applications (2022)
Journal Article
Güleç, F., Pekaslan, D., Williams, O., & Lester, E. (2022). Predictability of higher heating value of biomass feedstocks via proximate and ultimate analyses – A comprehensive study of artificial neural network applications. Fuel, 320, Article 123944. https://doi.org/10.1016/j.fuel.2022.123944

Higher heating value (HHV) is a key characteristic for the assessment and selection of biomass feedstocks as a fuel source. The HHV is usually measured using an adiabatic oxygen bomb calorimeter; however, this method can be time consuming and expensi... Read More about Predictability of higher heating value of biomass feedstocks via proximate and ultimate analyses – A comprehensive study of artificial neural network applications.