利用基于人工智能的新型模糊决策模型为电动汽车充电基础设施投资融资提出创新解决方案建议

IF 10.7 2区 计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Artificial Intelligence Review Pub Date : 2024-11-14 DOI:10.1007/s10462-024-11012-w
Gang Kou, Serkan Eti, Serhat Yüksel, Hasan Dinçer, Edanur Ergün, Yaşar Gökalp
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引用次数: 0

摘要

应确定为电动汽车充电基础设施投资提供有效融资的正确方法。然而,在文献中,对于哪种资金来源适合这些项目并没有达成共识。有必要开展一项新的研究,为这些项目推荐最合适的融资策略。因此,本研究的目的是找出电动汽车充电基础设施投资融资的创新解决方案。为实现这一目标,我们引入了一个新颖的模糊决策模型。首先,通过降维计算专家权重。其次,得到球形模糊决策矩阵。第三,利用球形模糊标准重要性和标准间相关性(CRITIC)对电动汽车充电基础设施的标准进行加权。第四,利用球形模糊排序技术,通过与最优方案的相似度几何平均值(RATGOS),对电动汽车充电基础设施融资的创新方案进行排序。本研究的主要贡献在于,通过建立新颖的决策模型,可以确定电动汽车充电基础设施投资融资的有效策略。现有文献中的大多数模型都没有考虑专家的权重。这种情况受到不同学者的批评,因为这些专家可能具有不同的资质。为了解决这一问题,本研究采用了机器学习的降维算法来计算专家权重。研究结果表明,电动汽车充电基础设施创新金融解决方案中最有效的标准是 "潜在收入"。根据排名结果,在电动汽车充电基础设施融资创新战略中,最具可持续性的解决方案是 "区块链技术"。
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Innovative solution suggestions for financing electric vehicle charging infrastructure investments with a novel artificial intelligence-based fuzzy decision-making modelling

The right methods for effective financing of electric vehicle charging infrastructure investments should be identified. However, in the literature, there is no consensus on which funding source would be right for these projects. There is a need for a new study to recommend the most appropriate financing strategy for these projects. Accordingly, the purpose of this study is to identify innovative solutions for financing electric vehicle charging infrastructure investments. A novel fuzzy decision-making model is introduced to reach this objective. Firstly, the weights of experts are calculated using dimension reduction. Secondly, Spherical fuzzy decision matrix is obtained. Thirdly, the criteria in charging infrastructure for electric vehicles are weighted using Spherical fuzzy criteria importance through intercriteria correlation (CRITIC). Fourthly, innovative solutions for financing electric vehicles charging infrastructure are ranked via Spherical fuzzy ranking technique by geometric mean of similarity ratio to optimal solution (RATGOS). The main contribution of this study is that effective strategies can be identified for financing electric vehicle charging infrastructure investments by establishing a novel decision-making model. Most of the existing models in the literature could not consider the weights of the experts. This condition is criticized by different scholar because these experts can have different qualifications. To satisfy this problem, in this study, dimension reduction algorithm with machine learning is taken into consideration to compute thee weights of the experts. The findings demonstrate that the most effective criterion in the innovative financial solution for the charging infrastructure of electric vehicles is determined as “potential income”. According to the ranking results, it is also defined that the most sustainable solution among the innovative strategies for financing the charging infrastructure of electric vehicles is “blockchain technology”.

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来源期刊
Artificial Intelligence Review
Artificial Intelligence Review 工程技术-计算机:人工智能
CiteScore
22.00
自引率
3.30%
发文量
194
审稿时长
5.3 months
期刊介绍: Artificial Intelligence Review, a fully open access journal, publishes cutting-edge research in artificial intelligence and cognitive science. It features critical evaluations of applications, techniques, and algorithms, providing a platform for both researchers and application developers. The journal includes refereed survey and tutorial articles, along with reviews and commentary on significant developments in the field.
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