Stochastic Approaches to Energy Markets: From Stochastic Differential Equations to Mean Field Games and Neural Network Modeling DOI Creative Commons
Luca Di Persio, Mohammed Alruqimi, Matteo Garbelli

et al.

Energies, Journal Year: 2024, Volume and Issue: 17(23), P. 6106 - 6106

Published: Dec. 4, 2024

This review paper examines the current landscape of electricity market modelling, specifically focusing on stochastic approaches, transitioning from Mean Field Games (MFGs) to Neural Network (NN) modelling. The central objective is scrutinize and synthesize evolving modelling strategies within power systems, facilitating technological advancements in contemporary market. emphasizes assessment model efficacy, particularly context MFG NN applications. Our findings shed light diversity models, offering practical insights into their strengths limitations, thereby providing a valuable resource for researchers, policy makers, industry practitioners. guides navigating leveraging latest techniques enhanced decision making improved operations.

Language: Английский

AI-driven participatory environmental management: Innovations, applications, and future prospects DOI Creative Commons
Márcia R. C. Santos, Luísa Cagica Carvalho

Journal of Environmental Management, Journal Year: 2025, Volume and Issue: 373, P. 123864 - 123864

Published: Jan. 1, 2025

The rapid advancement of Artificial Intelligence (AI) presents unprecedented opportunities for participatory environmental management. This paper explores the integration AI technologies into approaches, which engage diverse stakeholders in decision-making processes. Using artificial intelligence, a corpus 80 papers was compiled and subsequently analyzed with text mining tools. By identifying systematizing academics' contributions to knowledge about AI-driven tools, this study also discusses challenges ethical considerations inherent deployment, emphasizing need transparent, equitable, accountable systems. Looking ahead, we outline future prospects management, focusing on potential foster adaptive management strategies, enhance stakeholder collaboration, support sustainable development goals.

Language: Английский

Citations

2
Towards built environment Decarbonisation: A review of the role of Artificial intelligence in improving energy and Materials’ circularity performance DOI Creative Commons
Bankole Awuzie, A.B. Ngowi, Douglas Aghimien

et al.

Energy and Buildings, Journal Year: 2024, Volume and Issue: 319, P. 114491 - 114491

Published: June 28, 2024

Mitigating climate change challenges in the built environment through decarbonisation of energy and construction materials remains a pressing challenge. The circular economy (CE) has been identified as critical pathway to achieving this objective. CE promotes efficient use resources, extending their lifecycle minimising environmental impact using plethora methods. link between becomes evident when intertwined relationship materials, energy, is considered. By reducing waste ensuring continuous significantly lowers carbon emissions. This approach inherently aligned with overarching goals agenda. emergence digital technologies such artificial intelligence (AI) continued transform how activities are conducted improved. However, utility AI models engendering actualisation agenda improved performance within context under-researched. study addresses knowledge-practice gap, scientometric scoping analysis relevant peer-reviewed grey literature. Findings from revealed explored separately decarbonisation. Yet, studies exploring relation circularity for remain scant. narrative review further usefulness driving optimal levels across various economic sectors, including decision making which turn, encourages responsible producer consumer behaviour performance.

Language: Английский

Citations

5
Impact of Artificial Intelligence on Learning Management Systems: A Bibliometric Review DOI Creative Commons
Diego Vergara, Γεώργιος Λαμπρόπουλος, Álvaro Antón‐Sancho

et al.

Multimodal Technologies and Interaction, Journal Year: 2024, Volume and Issue: 8(9), P. 75 - 75

Published: Aug. 25, 2024

The field of artificial intelligence is drastically advancing. This study aims to provide an overview the integration into learning management systems. followed a bibliometric review approach. Specifically, following Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) statement, 256 documents from Scopus Web Science (WoS) databases over period 2004–2023 were identified examined. Besides analysis within existing literature, emerging themes topics identified, directions recommendations future research are provided. Based on outcomes, use systems offers adaptive personalized experiences, promotes active learning, supports self-regulated in face-to-face, hybrid, online environments. Additionally, enriched with can improve students’ engagement, motivation. Their ability increase accessibility ensure equal access education by supporting open educational resources was evident. However, need develop effective design approaches, evaluation methods, methodologies successfully integrate them classrooms emerged as issue be solved. Finally, further explore stakeholders’ literacy also arose.

Language: Английский

Citations

5
COVID-19 and Pandemic Preparedness in the Built Environment from a Scientometric Perspective DOI Creative Commons
Olusegun Aanuoluwapo Oguntona, Chijioke Emmanuel Emere, Ifije Ohiomah

et al.

COVID, Journal Year: 2025, Volume and Issue: 5(3), P. 30 - 30

Published: Feb. 25, 2025

The novel coronavirus (COVID-19) pandemic has become one of the most devastating epidemics recorded in world history. adverse impact is significant within architecture, engineering, and construction (AEC) industry other sectors economy. A considerable number COVID-19 research studies have been undertaken response to this global challenge across disciplines, with minimal output built environment. Thus, study aims identify, analyse, visualise trends AEC unfold sector’s readiness for possible future pandemics. employed scientometric approach explore outputs industry, an aspect health safety that not considered past owing nature pandemic. findings revealed USA, China, United Kingdom were top published countries affected as well. Co-occurring keywords analysis further showed predominant focus scholarly on subject around four clusters focusing sustainable resilience, pathways insights, land use energy strategies, indoor air excellence. Notwithstanding its limitations, establish need adopt innovative holistically practices event disasters provide a robust theoretical foundation researchers stakeholders environment, improving mitigative adaptive capacity potential occurrence

Language: Английский

Citations

0
AI-Driven Digital Twins for Enhancing Indoor Environmental Quality and Energy Efficiency in Smart Building Systems DOI Creative Commons
İbrahim Yitmen,

Amjad Almusaed,

Mohammed Bahreldin Hussein

et al.

Buildings, Journal Year: 2025, Volume and Issue: 15(7), P. 1030 - 1030

Published: March 24, 2025

Smart buildings equipped with diverse control systems serve the objectives of gathering data, optimizing energy efficiency (EE), and detecting diagnosing faults, particularly in domain indoor environmental quality (IEQ). Digital twins (DTs) offering an environmentally sustainable solution for managing facilities incorporated artificial intelligence (AI) create opportunities maintaining IEQ EE. The purpose this study is to assess impact AI-driven DTs on enhancing EE smart building (SBS). A scoping review was performed establish theoretical background about DTs, AI, IEQ, SBS, semi-structured interviews were conducted specialists industry obtain qualitative quantitative data gathered via a computerized self-administered questionnaire (CSAQ) survey, focusing how can improve SBS. results indicate that DT enhances occupants’ comfort energy-efficiency performance enables decision-making automatic fault detection maintenance conditioning buildings’ serviceability real time, response key industrial needs management (BEMS) interrogative predictive analytics maintenance. integration AI presents transformative approach improving practical implications advancement span across design, construction, policy domains, significant challenges need be carefully considered.

Language: Английский

Citations

0
Integrating large language models, reinforcement learning, and machine learning for intelligent indoor thermal comfort regulation DOI
Deli Liu, Feng Ling,

Xiaoping Zhou

et al.

Architectural Science Review, Journal Year: 2025, Volume and Issue: unknown, P. 1 - 14

Published: April 8, 2025

Language: Английский

Citations

0
The service trade with AI and energy efficiency: Multiplier effect of the digital economy in a green city by using quantum computation based on QUBO modeling DOI
Da Huo,

Wenjia Gu,

Dongmei Guo

et al.

Energy Economics, Journal Year: 2024, Volume and Issue: 140, P. 107976 - 107976

Published: Nov. 2, 2024

Language: Английский

Citations

2
Enhancing Visual Perception in Sports Environments: A Virtual Reality and Machine Learning Approach DOI Creative Commons

Taiyang Wang,

Peng Luo,

Sihan Xia

et al.

Buildings, Journal Year: 2024, Volume and Issue: 14(12), P. 4012 - 4012

Published: Dec. 19, 2024

The sports environment plays a crucial role in shaping the physical and mental well-being of individuals engaged activities. Understanding how environmental factors emotional experiences influence perceptions is essential for advancing public health research guiding optimal design interventions. However, existing studies this field often rely on subjective evaluations, lack objective validation, fail to provide practical insights applications. To address these gaps, study adopts data-driven approach. Quantitative data were collected explore visual badminton courts using eye-tracking technology semantic differential questionnaire. relationships between factors—such as illuminance (IL), height (Ht), roof saturation (RSa), slope (RS), backwall (BSa), natural materials proportion (BN)—and perception (W) analyzed. Furthermore, identifies best-performing machine learning model predicting perception, which subsequently integrated with genetic algorithm optimize thresholds. These findings actionable creating environments that enhance user experience support objectives.

Language: Английский

Citations

0
Stochastic Approaches to Energy Markets: From Stochastic Differential Equations to Mean Field Games and Neural Network Modeling DOI Creative Commons
Luca Di Persio, Mohammed Alruqimi, Matteo Garbelli

et al.

Energies, Journal Year: 2024, Volume and Issue: 17(23), P. 6106 - 6106

Published: Dec. 4, 2024

This review paper examines the current landscape of electricity market modelling, specifically focusing on stochastic approaches, transitioning from Mean Field Games (MFGs) to Neural Network (NN) modelling. The central objective is scrutinize and synthesize evolving modelling strategies within power systems, facilitating technological advancements in contemporary market. emphasizes assessment model efficacy, particularly context MFG NN applications. Our findings shed light diversity models, offering practical insights into their strengths limitations, thereby providing a valuable resource for researchers, policy makers, industry practitioners. guides navigating leveraging latest techniques enhanced decision making improved operations.

Language: Английский

Citations

0