Recent Progress in Sustainable Treatment Technologies for the Removal of Emerging Contaminants from Wastewater: A Review on Occurrence, Global Status and Impact on Biota DOI
Anu Mary Ealias,

Gayathri Meda,

Kashif Tanzil

et al.

Reviews of Environmental Contamination and Toxicology, Journal Year: 2024, Volume and Issue: 262(1)

Published: July 2, 2024

Language: Английский

Explainable Artificial Intelligence (XAI) DOI

Mitra Tithi Dey

Advances in environmental engineering and green technologies book series, Journal Year: 2024, Volume and Issue: unknown, P. 333 - 362

Published: Oct. 16, 2024

Explainable AI (XAI) is important in situations where decisions have significant effects on the results to make systems more reliable, transparent, and people understand how work. In this chapter, an overview of AI, its evolution are discussed, emphasizing need for robust policy regulatory frameworks responsible deployment. Then key concept use XAI models been discussed. This work highlights XAI's significance sectors like healthcare, finance, transportation, retail, supply chain management, robotics, manufacturing, legal criminal justice, etc. profound human societal impacts. Then, with integrated IoT renewable energy management scope smart cities addressed. The study particularly focuses implementations solutions, specifically solar power integration, addressing challenges ensuring transparency, accountability, fairness AI-driven decisions.

Language: Английский

Citations

137

Carbon neutrality: a comprehensive bibliometric analysis DOI
Lili Zhang, Jie Ling, Ming‐Wei Lin

et al.

Environmental Science and Pollution Research, Journal Year: 2023, Volume and Issue: 30(16), P. 45498 - 45514

Published: Feb. 17, 2023

Language: Английский

Citations

60

Artificial intelligence adoption in the physical sciences, natural sciences, life sciences, social sciences and the arts and humanities: A bibliometric analysis of research publications from 1960-2021 DOI Creative Commons
Stefan Hajkowicz, Conrad Sanderson, Sarvnaz Karimi

et al.

Technology in Society, Journal Year: 2023, Volume and Issue: 74, P. 102260 - 102260

Published: May 19, 2023

Analysing historical patterns of artificial intelligence (AI) adoption can inform decisions about AI capability uplift, but research to date has provided a limited view across various fields research. In this study we examine worldwide technology within 333 during 1960-2021. We do by using bibliometric analysis with 137 million peer-reviewed publications captured in The Lens database. define list 214 phrases developed expert working groups at the Organisation for Economic Cooperation and Development (OECD). found that 3.1 entire period were AI-related, surge practically all (physical science, natural life social science arts humanities) recent years. diffusion beyond computer was early, rapid widespread. 1960 14% related (many science), increased cover over half 1972, 80% 1986 98% current times. note experienced boom-bust cycles historically: "springs" "winters". conclude context appears different, interdisciplinary application is likely be sustained.

Language: Английский

Citations

55

AI-enabled metaheuristic optimization for predictive management of renewable energy production in smart grids DOI Creative Commons
S. Sankarananth,

M. Karthiga,

E. Suganya

et al.

Energy Reports, Journal Year: 2023, Volume and Issue: 10, P. 1299 - 1312

Published: Aug. 16, 2023

The integration of renewable energy sources into smart grids offers a promising solution for building sustainable and reliable systems. However, optimizing hybrid systems remains crucial area research. study presents comprehensive approach combining artificial intelligence algorithm techniques with metaheuristic optimization algorithms anticipating managing in grid environments. With precision, recall, accuracy scores 0.92, 0.93, respectively, the proposed Hybrid LSTM-RL model beats current correctly forecasting demand patterns. an 0.91 various load balancing measures, RL-SA efficiently measures balancing. mean squared error (MSE), absolute (MAE), R-squared score, root square (RMSE), percentage (MAPE) values 345.12, 15.07, 0.78, 18.57, 7.83, CNN-PSO also turns out to be most successful at generation energy. These discoveries help settings advance, enabling effective, dependable, economical production distribution. suggested has potential used rural off-grid settings. Overall, this research useful method maximizing acts as spark additional studies management

Language: Английский

Citations

48

Do the benefits outweigh the disadvantages? Exploring the role of artificial intelligence in renewable energy DOI
Meng Qin, Wei Hu, Xinzhou Qi

et al.

Energy Economics, Journal Year: 2024, Volume and Issue: 131, P. 107403 - 107403

Published: Feb. 12, 2024

Language: Английский

Citations

46

How does artificial intelligence affect high-quality energy development? Achieving a clean energy transition society DOI Creative Commons
Bo Wang, Jianda Wang, Kangyin Dong

et al.

Energy Policy, Journal Year: 2024, Volume and Issue: 186, P. 114010 - 114010

Published: Feb. 1, 2024

As China's energy development undergoes a process from qualitative improvements to quantitative changes, high-quality (HED) has become vital strategy of the Chinese government. representative emerging technologies, artificial intelligence (AI) can effectively promote clean transition, strengthen security, and enhance above process. Therefore, this paper explores relationship between AI HED based on gauging index level 30 provinces in China covering 2007–2017. In addition, we use green innovation R&D intensity as mediating variables study indirect effect HED. We further explore threshold digital economy The results indicate that positively affects China; specifically, every 1 % increase will lead 0.032 index. Moreover, indirectly increases by improving intensity. Further, shows influences impact This means have significantly positive areas with developed economy. Finally, provide practical approaches reference suggestions for achieve transition assistance AI.

Language: Английский

Citations

43

Will artificial intelligence make energy cleaner? Evidence of nonlinearity DOI
Chien‐Chiang Lee, Jingyang Yan

Applied Energy, Journal Year: 2024, Volume and Issue: 363, P. 123081 - 123081

Published: March 26, 2024

Language: Английский

Citations

39

Understanding the effects of artificial intelligence on energy transition: The moderating role of Paris Agreement DOI
Muhammad Zubair Chishti,

Xiqiang Xia,

Eyüp Doğan

et al.

Energy Economics, Journal Year: 2024, Volume and Issue: 131, P. 107388 - 107388

Published: Feb. 6, 2024

Language: Английский

Citations

34

Impact of artificial intelligence on renewable energy supply chain vulnerability: Evidence from 61 countries DOI
Yuegang Song, Ziqi Wang,

Changqing Song

et al.

Energy Economics, Journal Year: 2024, Volume and Issue: 131, P. 107357 - 107357

Published: Feb. 19, 2024

Language: Английский

Citations

26

Information communication technology, economic growth, natural resources, and renewable energy production: Evaluating the asymmetric and symmetric impacts of artificial intelligence in robotics and innovative economies DOI
Muhammad Qamar Rasheed, Yuhuan Zhao, Zahoor Ahmed

et al.

Journal of Cleaner Production, Journal Year: 2024, Volume and Issue: 447, P. 141466 - 141466

Published: Feb. 26, 2024

Language: Английский

Citations

21