This page provides an English interface to the gxceed GX paper corpus. The corpus aggregates papers from 13 open 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 21–40 of 987 papers
T. Sindhu, Dr. K. Sivakumar, Dr. D. Jayanthi +2
This review examines geospatial technologies (GIS, remote sensing, UAV, LiDAR) combined with machine learning for carbon stock estimation in mango orchards. Integration of satellite imagery and ML models (Random Forest, SVM, ANN) improves p…
Jian-yun Lu, Qing-Yi Liu, Yu-Qi Wang +5
This study develops a Bayesian multiobjective optimization framework with Gaussian process surrogates and uncertainty-aware search to map trade-offs in pharmaceutical wastewater treatment. Optimized operating windows improve removal efficie…
Qian Ma, Chunxiao Liu, Kui Huang +6
This paper proposes D-PGNet, a deep projected gradient network that accelerates low-carbon economic dispatch with energy storage and carbon trading costs. It embeds physical constraints as differentiable projection layers, achieving optimal…
Le Sun, Jia Liu, Kuanhou Tian
Using Chinese A-share listed firms from 2008-2024, this study finds that low-carbon transition strategy disclosure increases analyst following. The effect is driven by enhanced investor relations and richer information environment, but mana…
Winda Wulandari, Sri Widyastuti, Harnovinsah Harnovinsah +1
This systematic literature review reconceptualizes financial reporting integrity as a socio-technical governance phenomenon shaped by governance accountability, sustainability legitimacy, and technological transparency. Analyzing 28 Scopus …
Yaacob Ibrahim, Khaled Hussainey, Taghred Mokhtar Sayed Moawad
This study examines whether carbon exposure affects corporate borrowing costs in the MENA region using a panel of 771 firm-year observations from 2016 to 2023. Combining fixed effects, IV, GMM, quantile regression, and machine learning, it …
Cristian Valentin Hapenciuc, Daniela Mihaela NEAMTU, Teodora Cajvan +1
This study applies FinBERT to financial news text to analyze the impact of ESG narratives on market volatility. Focusing on tech, energy, and banking sectors in Eastern Europe, it finds signs of a 'regime shift' where ESG transitions from a…
D. Barro, A. Basso, M. Corazza +1
This study uses machine learning to analyze the impact of the energy transition on Eurozone sovereign credit risk. It evaluates how the shift to renewable energy affects government bond yields and CDS spreads, offering insights into the imp…
Simona Epasto, Maria Lúcia, Masiel Melissa Pereira
This paper examines AI integration in agrivoltaic systems, focusing on socio-territorial implications for rural landscapes. Through case studies including the European SYMBIOSYST project and GIS/UAV geospatial monitoring, it analyzes how pr…
Ke W
This paper frames environmental monitoring as collaborative governance infrastructure under ESG and net-zero policies, and explores how 'Quantum Intelligence (QI)'—combining quantum optimization and quantum machine learning—can reshape the …
(著者不明)
This paper demonstrates that integrating IoT and BI platforms improves Scope 3 emissions reporting accuracy by 40% in logistics. It emphasizes data unification from a governance perspective, offering new possibilities for carbon tracking an…
Minyou Qing, Suhaiza Zailani
This review systematically analyzes the application of AI-driven practices in road freight transport (RFT) decarbonization. Following the SPAR-4-SLR protocol, 227 articles were reviewed using bibliometric analysis and science mapping. Publi…
Seyed Ali Hosseini, Francesco Grimaccia, A. Niccolai
This paper introduces fuzzy logic into reward design for deep reinforcement learning agents in carbon emission trading (ETS), aiming to optimize trading strategies. Fuzzy rewards improve decision-making under uncertainty, balancing emission…
Xueqing Wang, Lang Wang
Using Chinese A-share listed firms from 2010-2023, this study shows climate risk exacerbates green innovation bubbles—a divergence between patent quantity and quality. Managerial myopia and financing constraints are key channels, while digi…
Md Qamruzzaman
Using panel regressions and a deep learning (MLP) model on 62 listed Bangladeshi financial institutions (2005-2023, 1,178 firm-years), this study finds that intellectual, human, and natural capital disclosures each positively and significan…
Alfredo Merlet
This replication package constructs a Say-Do Gap Index for IBEX 35 firms (2019-2025) using a fine-tuned Spanish BERT (BETO) to detect unverified ESG commitments from media sources. It links the index to firm value (Tobin's Q, ROA, ROE) via …
Sina Rostami, Muhammad Bilal, Mehrdad Taghipour
This scoping review systematically maps technologies and strategies to reduce energy use and carbon footprints in operating rooms, evaluating methods from HVAC optimization to AI-driven management. It identifies a gap in kinetic energy harv…
Pengfei Zhang, Pan Liu, Li Jiang +1
This paper proposes a cooperative game-based low-carbon operation strategy for multi-microgrids using multi-agent deep reinforcement learning. It introduces an energy-carbon-green certificate P2P trading mechanism and Nash bargaining for fa…
Venkata Krishna Reddy, Aadam Quraishi, G. C. Prashant +1
This paper proposes a deep learning-based decision support system (DSS) for renewable energy (RE) investment and deployment. It uses CNNs to extract features from weather, energy, and economic data, RNNs to forecast energy demand and supply…
Lila Simon, Abino Simon, Aalbin Simon
This chapter explores the integration of AI and renewable energy for a sustainable energy ecosystem. It reviews the renewable landscape in India and globally, detailing AI applications in solar, wind, hydro, biomass, and geothermal, includi…
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