Toward Energy Transformation: Intelligent Decision-Making Model Based on Uncertainty Neutrosophic Theory

Mona Mohamed, Nissreen A. S. El-Saber
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Abstract

There has been an increasing tendency for the generation of energy from diverse renewable resources because of the application of contemporary pollution mitigation and justification regulations. Precisely a consequence, choosing the best renewable energy source might be considered a challenging issue given the complexity of the future conditions in any society. Environmental, economic, social, and technical aspects are merely some of the factors that are taken into consideration while evaluating renewable energy sources (RnESs). The suitable RES selection problem, which relies on ambiguous and imprecise data, is also influenced by a variety of circumstances. Hence, this study constructs multi-stages intelligent decision-making model (MsIDMM) based on multi-criteria decision making (MCDM) with support with neutrosophic theory especially, interval valued neutrosophic sets to rank the sources of renewable energy. Ultimately, combinative distance-based assessment (CODAS) method under interval-valued neutrosophic sets is used to rank the sources of renewable energy.
迈向能源转型:基于不确定性中性理论的智能决策模型
由于当代污染缓解和正当法规的应用,利用各种可再生资源生产能源的趋势日益明显。因此,鉴于任何社会未来条件的复杂性,选择最佳的可再生能源可能被认为是一个具有挑战性的问题。环境、经济、社会和技术方面只是评估可再生能源(RnES)时要考虑的部分因素。合适的可再生能源选择问题依赖于模糊和不精确的数据,也受到各种情况的影响。因此,本研究在多标准决策(MCDM)的基础上构建了多阶段智能决策模型(MsIDMM),并利用中性理论(尤其是区间值中性集)对可再生能源进行排序。最终,在区间值中性集下使用基于距离的组合评估(CODAS)方法对可再生能源进行排序。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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