Assessing technology portfolios of clean energy-driven desalination-irrigation systems with interval-valued intuitionistic fuzzy sets

Hu, Kejia; Tan, Qian; Zhang, Tianyuan; Wang, Shuping

doi:10.1016/j.rser.2020.109950

Cited by 28 publications

(11 citation statements)

References 81 publications

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“…Building on IFS, many MCDM methods have been proposed one after another, such as a novel EDAS approach for assessment of healthcare waste disposal technology [28], a new approach to multi-criteria decision-making [29] and the ELECTRE multi-criteria analysis approach for ranking alternatives [30]. Alternatively, IFS has found an increasingly wide utilization in a wide range of fields, such as image fusion [31], pattern recognition [32] and energy evaluation [33]. Moreover, considering that a single membership degree may not express the decision information well in some situations.…”

Section: Fuzzy Sets and Fuzzy Preference Relationsmentioning

confidence: 99%

Ranking Tourist Attractions through Online Reviews: A Novel Method with Intuitionistic and Hesitant Fuzzy Information Based on Sentiment Analysis

Qin

Wang

Zhang

2021

Int. J. Fuzzy Syst.

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Online tourist reviews are the real feeling of tourists after the journey, which have a strong reference value for potential tourists to make travel decisions. However, it is almost impossible for a potential tourist to look through the massive online reviews related to tourist attractions (TAs) so that he/she can make the most appropriate decision. To this end, this paper proposes a recommender system to rank the alternative TAs through online reviews based on aspect-level sentiment analysis and multi-criteria decision-making (MCDM) with intuitionistic and hesitant fuzzy information. In this methodology, the aspects that the experienced tourists concern are extracted from online reviews to construct a three-level evaluation system (including target layer, criteria layer and sub-criteria layer), which not only ensures the comprehensive evaluation of TAs as much as possible, but also reduces the complexity of the decision-making process. Then, the online reviews related to these sub-criteria are transformed into the corresponding intuitionistic and hesitant fuzzy performance scores through aspect-level sentiment analysis. Furthermore, in order to obtain the final ranking result that more in line with the expectations of the potential tourist, the preference information from the potential tourist and experienced tourists is integrated to determine the weights of criteria. Subsequently, the intuitionistic and hesitant fuzzy TOPSIS (IHF-TOPSIS) method is proposed to rank the alternative TAs. Finally, a case study is provided to verify the validity and applicability of the methodology.

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Section: Fuzzy Sets and Fuzzy Preference Relationsmentioning

confidence: 99%

Ranking Tourist Attractions through Online Reviews: A Novel Method with Intuitionistic and Hesitant Fuzzy Information Based on Sentiment Analysis

Qin

Wang

Zhang

2021

Int. J. Fuzzy Syst.

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“…Atanassov [23,24] first proposed the concept of intuitionistic fuzzy sets (IFSs) in 1986 and expanded it into interval-valued intuitionistic fuzzy sets (IVIFSs) in 1989, which carve out the vagueness of realistic decisions through mathematical thinking. IFSs and IVIFSs have been widely used in e-commerce [25], social networks [26], clean energy [27], industrial engineering [28], and other fields. The interval numbers expressing the three states of support, opposition, and neutrality can be used to express membership degree, non-membership degree, and hesitancy degree, which is more flexible and delicate in dealing with vagueness and uncertainty.…”

Section: Literature Reviewmentioning

confidence: 99%

“…The positive and negative ideal solutions are determined by combining Equations ( 24) and ( 25), based on the data in T = t ij 5×7 . The distance between the candidate partner and the positive and negative ideal solution is calculated according to Equations ( 26) and (27). The gray correlation degree between the candidate partners and the positive and negative ideal solutions is calculated according to Equations ( 28)- (31).…”

Section: Numerical Examplesmentioning

confidence: 99%

A Cooperative Partner Selection Study of Military-Civilian Scientific and Technological Collaborative Innovation Based on Interval-Valued Intuitionistic Fuzzy Set

Zhang

2021

Symmetry

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Military-civilian scientific and technological collaborative innovation (MCSTCI) is an important intersection of civil-military integrated development strategies and innovation-driven development strategies, and has become a brand-new model for Chinese key scientific and technological research. The selection of cooperative partner between military and civilian innovation entities is not only the primary segment to carry out MCSTCI activities, but also an important foundation for achieving complementary advantages and win-win cooperation. Therefore, on the basis of summarizing and combing the evaluation indicators, a partner selection model based on interval-valued intuitionistic fuzzy set multi-attribute decision-making is proposed. Firstly, we improve the traditional scoring function, and combine the new scoring function and entropy weight method to determine the weight of each evaluation indicator. Secondly, considering the impact of decision-makers’ risk attitudes, a method of transforming evaluation matrix based on hesitancy distribution is proposed. Finally, the grey correlation and TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution) method is used to mark and rank the candidates, and the innovation entities with the highest score is selected as the collaborative innovation partner. An example of a military equipment manufacturing enterprise in Beijing for partner selection in order to carry out joint technological research on a certain anti-ship missile weapon shows that the model is more comprehensive and flexible in solving fuzzy multi-attribute decision-making problems, and can assess and select cooperative partners for MCSTCI scientifically and objectively.

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“…Intuitionistic fuzzy sets (IFSs) and interval-valued intuitionistic fuzzy sets (IVIFSs), both of which are extensions of fuzzy sets, can retain fuzzy information better than fuzzy sets and have been successfully applied in the fields of cluster analysis, multi-attribute decision-making, and pattern recognition [14][15][16][17][18]. To measure uncertainty in multi-attribute decision-making, Liu et al [19] converted IVIFSs to three interval vectors and proposed a new distance measure of IVIFSs based on the distance of interval number.…”

Section: Introductionmentioning

confidence: 99%

Robustness of Interval-Valued Intuitionistic Fuzzy Reasoning Quintuple Implication Method

et al. 2022

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Assessing technology portfolios of clean energy-driven desalination-irrigation systems with interval-valued intuitionistic fuzzy sets

Cited by 28 publications

References 81 publications

Ranking Tourist Attractions through Online Reviews: A Novel Method with Intuitionistic and Hesitant Fuzzy Information Based on Sentiment Analysis

Ranking Tourist Attractions through Online Reviews: A Novel Method with Intuitionistic and Hesitant Fuzzy Information Based on Sentiment Analysis

A Cooperative Partner Selection Study of Military-Civilian Scientific and Technological Collaborative Innovation Based on Interval-Valued Intuitionistic Fuzzy Set

Robustness of Interval-Valued Intuitionistic Fuzzy Reasoning Quintuple Implication Method

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