This page provides an English interface to the gxceed GX paper corpus. The corpus aggregates papers from 14 contributing scholarly metadata sources and uses AI-assisted classification to identify signals related to measurement, policy narratives, outcomes, implementation, industrial adoption, and verification.
The goal is not only to discover papers, but to observe how GX research is distributed across research substance, implementation narratives, external expectations, implementation substance, and judgment formation.
Summaries are AI-assisted. Always refer to the original paper for authoritative conclusions.
Showing 941–943 of 943 papers
Yingfeng Wei, Hui Chen, Ye Tian +9
This study proposes a hybrid forecasting framework integrating VMD-SE, Transformer, and BiLSTM, optimized by QPSO, for short-term air conditioning load in industrial buildings. Validated on real datasets from Hubei, China, the model achieve…
(著者不明)
This paper proposes an integrated approach to improve urban energy efficiency by combining spatial analysis (GIS mapping, regression) with policy interventions. Using cases from Kerala (India), Loures (Portugal), and Iran, it identifies hig…
Kshitij Bhatta, Muhammad Waseem, Mingzhe Liu +3
This paper proposes a digital twin framework for wood drying in desiccant-assisted heat pump (DAHP) systems. Combining high-fidelity physics models with multi-agent reinforcement learning (MARL), it reduces total energy consumption by 43.2%…
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