Data science and big data analytics: A systematic review of methodologies used in the supply chain and logistics research

H Jahani, R Jain, D Ivanov - Annals of Operations Research, 2023 - Springer
Data science and big data analytics (DS &BDA) methodologies and tools are used
extensively in supply chains and logistics (SC &L). However, the existing insights are …

Forecasting energy use in buildings using artificial neural networks: A review

J Runge, R Zmeureanu - Energies, 2019 - mdpi.com
During the past century, energy consumption and associated greenhouse gas emissions
have increased drastically due to a wide variety of factors including both technological and …

Data analytics in the supply chain management: Review of machine learning applications in demand forecasting

A Aamer, LP Eka Yani… - Operations and Supply …, 2020 - journal.oscm-forum.org
In today's fast-paced global economy coupled with the availability of mobile internet and
social networks, several business models have been disrupted. This disruption brings a …

Systematic review of deep learning and machine learning for building energy

S Ardabili, L Abdolalizadeh, C Mako, B Torok… - Frontiers in Energy …, 2022 - frontiersin.org
The building energy (BE) management plays an essential role in urban sustainability and
smart cities. Recently, the novel data science and data-driven technologies have shown …

An optimized nonlinear grey Bernoulli prediction model and its application in natural gas production

C Liu, T Lao, WZ Wu, W **e, H Zhu - Expert Systems with Applications, 2022 - Elsevier
Natural gas, an efficient, eco-friendly and clean green energy, has become one of the
important energy structures of various countries in the world, accurately predicting the …

Natural gas consumption forecasting: A discussion on forecasting history and future challenges

J Liu, S Wang, N Wei, X Chen, H **e, J Wang - Journal of Natural Gas …, 2021 - Elsevier
Natural gas consumption forecasting technology has been researched for 70 years. This
paper reviews the history of natural gas consumption forecasting, and discusses the …

Principles, research status, and prospects of feature engineering for data-driven building energy prediction: A comprehensive review

Z Wang, L **a, H Yuan, RS Srinivasan… - Journal of Building …, 2022 - Elsevier
With the rapid growth in the volume of relevant and available data, feature engineering is
emerging as a popular research subject in data-driven building energy prediction owing to …

Using machine learning tools for forecasting natural gas consumption in the province of Istanbul

OF Beyca, BC Ervural, E Tatoglu, PG Ozuyar, S Zaim - Energy Economics, 2019 - Elsevier
Commensurate with unprecedented increases in energy demand, a well-constructed
forecasting model is vital to managing energy policies effectively by providing energy …

An active approach to heat transfer enhancement in indirect heaters of city gate stations: an experimental modeling

AA Delouei, H Naeimi, H Sajjadi, M Atashafrooz… - Applied Thermal …, 2024 - Elsevier
A major problem with gas pressure reduction stations is the very low thermal efficiency of
indirect water bath heaters (IWBHs) used to prevent gas hydration. In this study, an …

Energy prediction techniques for large-scale buildings towards a sustainable built environment: A review

AAA Gassar, SH Cha - Energy and Buildings, 2020 - Elsevier
Building energy prediction techniques are the primary tool for moving towards sustainable
built environments. Energy prediction models play irreplaceable roles in making energy …