The authors would like to make the following corrections about the published paper [...]
İlayda Nur Şişman, Burcu Çarklı Yavuz
The transportation sector is a major contributor to global greenhouse gas emissions, making electric vehicle (EV) adoption critical for decarbonization. This study investigates EV adoption determinants in Turkey using explainable machine learning, focusing on economic, infrastruc…
This study examines corporate carbon emissions of Korean firms from an ESG perspective and develops an AI-based screening framework to improve the identification of firms likely to exceed regulatory emission thresholds. As global climate policies and carbon pricing mechanisms exp…
Reny Sukmawani, Sri Ayu Andayani, Mai Fernando Nainggolan, Wa Ode Al Zarliani, Endang Tri Astutiningsih
Accurate prediction of food consumption is essential for strengthening regional food security planning, particularly in areas experiencing increasing food demand and environmental uncertainty. This study aims to predict food consumption patterns in Sukabumi Regency, West Java, In…
Mei Bie, Siyu Chen, Yongli Wang, Kai Song
While artificial intelligence (AI) can improve energy efficiency in carbon neutrality applications, its high energy consumption and rebound effect weaken the actual emission reduction effect. To address the issues of high energy consumption and the rebound effect of AI weakening…
U.S. renewable energy consumption has expanded substantially over the past five decades, but this transition cannot be adequately characterized by aggregate growth alone. This study developed an integrated empirical, forecasting, uncertainty, reconciliation, scenario, and plannin…
Mohammed Almubarak, Md Ismail Hossain, Md Shafiullah
This paper evaluates neural-network approaches for lithium-ion battery state-of-charge (SoC) estimation under a unified pipeline, fixed data partitions, and identical preprocessing. We study FNNs trained with Levenberg–Marquardt (LM), Bayesian Regularization (BR), and Scaled Conj…