A multi‐criteria sustainable supplier selection framework based on neutrosophic fuzzy data and entropy weighting

Zeng, Shouzhen; Hu, Yingjie; Baležentis, Tomas; Štreimikienė, Dalia

doi:10.1002/sd.2096

Cited by 65 publications

(30 citation statements)

References 43 publications

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“…However, although in the literature, some efforts used different methods to evaluate green growth efficiency and indicators. However, a few previous studies employed the Multiple Criteria Decision Making (MCDM) and fuzzy sets theory to assess green growth indicators (Su, Zhang, Zhang, & Streimikiene, 2020; Zeng, Hu, Balezentis, & Streimikiene, 2020; Zrobek, Kovalyshyn, Renigier‐Biłozor, Kovalyshyn, & Kovalyshyn, 2020). Particularly, there is no study in the current body of the literature regarding the application of fuzzy sets and MCDM methods in the field of green growth.…”

Section: Introductionmentioning

confidence: 99%

Evaluating the green growth indicators to achieve sustainable development: A novel extended interval‐valued intuitionistic fuzzy‐combined compromise solution approach

Alrasheedi

Mardani

Mishra³

et al. 2020

Sustainable Development

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Recent years have witnessed the green growth as a renowned efficient approach to tracking the progress towards sustainable development. The paper is mainly aimed to propose an innovative extended approach based on Combined Compromise Solution (CoCoSo) and Interval‐Valued Intuitionistic Fuzzy Set (IVIFS); thus, it is called IVIF Combined Compromise Solution (IVIF‐CoCoSo). This study is the first effort that used the fuzzy sets theory and decision‐making technique (entitled IVIF‐CoCoSo) to rank and evaluate the indicators of green growth to sustainable manufacturing in the manufacturing sector. To reach the study objectives, a total of five indicators and 30 sub‐indicators for evaluation of green growth are collected from the existing literature review. Subsequently, this study has been extended using the IVIF‐CoCoSo approach for ranking, modeling, and evaluating the green growth indicators into sustainable manufacturing based on experts' opinions. The results of this study showed that the environmental and resource productivity of the economy indicators is more significant than the other indicators in the manufacturing sector. Moreover, findings confirmed the accuracy of the proposed method in solving the green growth problem, and comparison was also made between the results of the proposed method and some other Multi‐Criteria Decision Making (MCDM) methods.

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Section: Introductionmentioning

confidence: 99%

Evaluating the green growth indicators to achieve sustainable development: A novel extended interval‐valued intuitionistic fuzzy‐combined compromise solution approach

Alrasheedi

Mardani

Mishra³

et al. 2020

Sustainable Development

Self Cite

View full text Add to dashboard Cite

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“…Machine learning-based method uses its self-learning ability to obtain some hidden features of echo changes and shows good memory and association ability [19,20]. It has been applied as classification model and numerical prediction model in weather forecast, showing the potential and broad prospects of applying neural network model to radar echo extrapolation [21,22].…”

Section: Introductionmentioning

confidence: 99%

Prediction of Short-Time Rainfall Based on Deep Learning

Sun

Huang

et al. 2021

Mathematical Problems in Engineering

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Short-time heavy rainfall is a kind of sudden strong and heavy precipitation weather, which seriously threatens people’s life and property safety. Accurate precipitation nowcasting is of great significance for the government to make disaster prevention and mitigation decisions in time. In order to make high-resolution forecasts of regional rainfall, this paper proposes a convolutional 3D GRU (Conv3D-GRU) model to predict the future rainfall intensity over a relatively short period of time from the machine learning perspective. Firstly, the spatial features of radar echo maps with different heights are extracted by 3D convolution, and then, the radar echo maps on time series are coded and decoded by using GRU. Finally, the trained model is used to predict the radar echo maps in the next 1-2 hours. The experimental results show that the algorithm can effectively extract the temporal and spatial features of radar echo maps, reduce the error between the predicted value and the real value of rainfall, and improve the accuracy of short-term rainfall prediction.

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“…Yang et al [9] proposed the belief and plausibility measure on IFSs with construction of belief-plausibility TOPSIS. Faizi et al [10] used the characteristic objects method for multicriterian group decision-making problems through IFSs and Zeng et al [11] proposed a fuzzy methodology, neutrosophic fuzzy set, for sustainable supplier selection based on fuzzy information.…”

Section: Introductionmentioning

confidence: 99%

Complex T-Spherical Fuzzy Relations With Their Applications in Economic Relationships and International Trades

et al. 2021

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Uncertainty is the unavoidable part of the life. In almost all circumstances, we regularly find ourselves in a state of uncertainty. Several reasons can lead to uncertainty, such as randomness, vagueness and rough knowledge. Fuzzy set (FS) theory deals with these kinds of information. Many generalizations had been made in the theory of FSs, such as intuitionistic FSs (IFSs), q-rung orthopair FSs (qROFSs), complex qROFSs (CqROFSs), spherical FSs (SFSs), T-spherical FSs (TSFSs), and complex TSFSs (CTSFSs). Among these generalizations of FSs, the CTSFSs are the most dominant generalization of the FSs. Although fuzzy relations (FRs), IF relations (IFRs) and complex FRs (CFRs) were defined in the literature, the concepts of relations have not yet been introduced in the CTSFSs. This paper unveils the novel concept of CTSF relations (CTSFRs), which provides the extensive generalizations of FRs. The proposed CTSFRs can give many generalized types of FRs, such as IFRs, CFRs, Pythagorean FRs, qROFRs, SFRs and TSFRs, etc. Additionally, some useful properties and results are obtained for CTSFRs. Moreover, a couple of applications demonstrate the usefulness of the proposed concepts. These CTSFRs can be used to depict the time-related interdependence of global market. Thus, we apply these CTSFRs to analyze the interdependence of the international trades among countries and compare the financial factors affecting business markets. Furthermore, the economic relationships with respect to time lag can be modeled by using the CTSFSs and the CTSFRs. Finally, a comparative analysis illuminates the supremacy of the proposed way in contrast with the existing ones.INDEX TERMS Fuzzy sets (FSs); T-spherical FSs (TSFSs); Complex TSFSs (CTSFSs); CTSF relations (CTSFRs); Cartesian product in CTSFSs; CTSF composite relation; Financial and economic relationships.

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A multi‐criteria sustainable supplier selection framework based on neutrosophic fuzzy data and entropy weighting

Cited by 65 publications

References 43 publications

Evaluating the green growth indicators to achieve sustainable development: A novel extended interval‐valued intuitionistic fuzzy‐combined compromise solution approach

Evaluating the green growth indicators to achieve sustainable development: A novel extended interval‐valued intuitionistic fuzzy‐combined compromise solution approach

Prediction of Short-Time Rainfall Based on Deep Learning

Complex T-Spherical Fuzzy Relations With Their Applications in Economic Relationships and International Trades

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