Nuclear power: Analysis using fuzzy multidimensional similarity measures

In this paper, we discuss the importance of nuclear power for the future of the world with respect to climate change. In particular, we examine the involvement of nuclear power by countries in several different ways. We consider first the involvement of countries with respect to the amount of nuclear power produced, global energy transition, and capacity factor. Countries are ranked with respect to these three involvement areas. The fuzzy similarity measures of these rankings are found to be low in most cases. We next place countries in their respective regions. We rank the countries with respect to their carbon dioxide emissions and their greenhouse gas emissions. We then determine the fuzzy similarity measures of the countries with respect to the rankings. We found that one of the fuzzy similarity measures involving green house gas emissions is high.

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Publication Details

Journal
Journal of algebraic hyperstructures and logical algebras
Published
2025-01-01
DOI
https://doi.org/10.61838/kman.jahla.6.2.2
Citations
1
Primary Topic
Multi-Criteria Decision Making
Type
article
Field-Weighted Citation Impact
2.11
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article

Nuclear power: Analysis using fuzzy multidimensional similarity measures

John N. Mordeson, Sunil Mathew, D. S. Malik
1 citations
Journal of algebraic hyperstructures and logical algebras
Multi-Criteria Decision Making
2.11
article

Nuclear power: Analysis using fuzzy multidimensional similarity measures

John N. Mordeson, Sunil Mathew, D. S. Malik
article en
1 citations

Abstract

In this paper, we discuss the importance of nuclear power for the future of the world with respect to climate change. In particular, we examine the involvement of nuclear power by countries in several different ways. We consider first the involvement of countries with respect to the amount of nuclear power produced, global energy transition, and capacity factor. Countries are ranked with respect to these three involvement areas. The fuzzy similarity measures of these rankings are found to be low in most cases. We next place countries in their respective regions. We rank the countries with respect to their carbon dioxide emissions and their greenhouse gas emissions. We then determine the fuzzy similarity measures of the countries with respect to the rankings. We found that one of the fuzzy similarity measures involving green house gas emissions is high.

Journal of algebraic hyperstructures and logical algebrasVol. 6(2)
Creighton University (US), National Institute of Technology Calicut (IN)
Climate action
Openalex Percentile: Top 12%
Multi-Criteria Decision Making
2.11
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Nuclear power: Analysis using fuzzy multidimensional similarity measures — John N. Mordeson, Sunil Mathew, et al. · Journal of algebraic hyperstructures and logical algebras (2025) | TGRS Research Map | TGRS