A Comparative Study Between Lebanon and Middle East Countries Based on Data Mining Techniques

Katat, Souha el; Kalakech, Ali; Kalakech, Mariam; Hamad, Denis

doi:10.1109/acit.2018.8672723

Cited by 3 publications

(1 citation statement)

References 5 publications

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“…Renewable energy consumption (% of total final energy consumption) K 3 Carbon dioxide emissions (Per capita (tons)) K 4 Carbon dioxide emissions (kg per 2010 US$ of GDP) K 5 Forest area (% of total land area) K 6 Forest area (Change (%)) K 7 Natural resource depletion (% of GNI) K 8 Household and ambient air pollution (per 100,000 population) K 9…”

Section: Resultsmentioning

confidence: 99%

Evaluating Environmental Sustainability Position of Turkey Via Bric and Mint Countries With K-Nn Algorithm

Eren¹

2020

FCPE

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Environmental sustainability is one of the biggest difficulties met by humanity. It is also one pillar of sustainable development purposes required to be executed. For evaluating and comparing all world countries with respect to this perspective, an index is derived from the United Nations. With this index, the countries of the world are divided into four categories, such as "Very High Developed (VHD)", "High Developed (HD)", "Medium Developed (MD)" and lastly, "Low Developed (LD)". According to the 2019 environmental sustainable index value, Turkey is located in the VHD category. Some of the experts put forward that Turkey will compete with economic giants in 2050. Our hope economically continued efforts will be achieved environmentally also. These thoughts became the starting point of this study. With this aim, the position of Turkey is predicted with the BRIC and MINT countries data regarding to environmental sustainability with the k-NN (Nearest Neighbor) algorithm technique.

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Section: Resultsmentioning

confidence: 99%

Evaluating Environmental Sustainability Position of Turkey Via Bric and Mint Countries With K-Nn Algorithm

Eren¹

2020

FCPE

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Artificial Intelligence is Transforming the World Development Indicators

Ashtaiwi

2020

2020 IEEE / ITU International Conference on Artificial Intelligence for Good (AI4G)

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Artificial Intelligence for Sustainability: A Systematic Literature Review in Information Systems

Siqueira,

Santos,

Diniz

et al. 2024

RGSA

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Objective: It is vital to investigate how technologies benefit or impair sustainable development. This review aimed to provide updated literature on Artificial Intelligence (AI), in explicit connection with sustainability. Theoretical Framework: This article performs a systematic literature review of information systems (IS) journals on AI employment in promoting sustainable development (SD). Method: Among 331 articles, 97 have been identified in the Scopus and Web of Science databases from 2017 to 2022 focusing on the AI use for environmental, economic, legal political, organizational, and social development. Results and Discussion: According to the findings, the identified areas of interest and respective papers were associated with the corresponding concepts and summarized. These studies point to the role of AI in supporting decision-making and reveal research avenues in information and communication technologies (ICTs) and SD. The authors also propose a framework correlating the concepts with the 17 Sustainable Development Goals (SDGs). Research Implications: The practical and theoretical implications of this research were discussed, providing insights into how the results can be applied or influence practices in the field of ICTs and SD. Originality/Value: The relevance and value of this research are evidenced by highlighting the contributions research in the IS field has made regarding AI for SD since 2017. As a step forward in this literature review, the authors suggest a research agenda for the IS field.

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A Comparative Study Between Lebanon and Middle East Countries Based on Data Mining Techniques

Cited by 3 publications

References 5 publications

Evaluating Environmental Sustainability Position of Turkey Via Bric and Mint Countries With K-Nn Algorithm

Evaluating Environmental Sustainability Position of Turkey Via Bric and Mint Countries With K-Nn Algorithm

Artificial Intelligence is Transforming the World Development Indicators

Artificial Intelligence for Sustainability: A Systematic Literature Review in Information Systems

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