Identifying and prioritizing factors affecting in-cabin passenger comfort on high-speed rail in China: A fuzzy-based linguistic approach

Chen, Zhen‐Song; Liu, Xiaolu; Rodríguez, Rosa M.; Wang, Xianjia; Chin, Kwai‐Sang; Tsui, Kwok‐Leung; Martínez, Luis

doi:10.1016/j.asoc.2020.106558

Cited by 59 publications

(35 citation statements)

References 77 publications

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“…(5-7) overcomes the shortcomings of the above-mentioned distance Eqs. (1)(2)(3)(4), satisfies the definition of distance, and fully considers the differences in their membership degrees, as well as the differences in length and probability. For Example 2, using the new Hamming distance to calculate, we can get: d nh (h(p), h 1 (p)) = 0.05, d nh (h(p), h 2 (p)) = 0.06.…”

Section: Proof (1)nonnegativementioning

confidence: 99%

“…Multi-attribute decision-making (MADM) problems are becoming more and more common in human social activities. For example, it could be applied to site selection assessment [1], hotel selection [2], passenger demand and service quality of High-speed rail [3,4], sustainable supplier selection [5], and so on. Decision makers (DMs) solve MADM problems based on their own values, preferences and knowledge system.…”

Section: Introductionmentioning

confidence: 99%

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Multi-Attribute Decision-Making Method Based Distance and COPRAS Method with Probabilistic Hesitant Fuzzy Environment

Song¹,

Chen²

2021

IJCIS

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As an extension of hesitant fuzzy set, the probabilistic hesitant fuzzy set (PHFS) can more accurately express the initial decision information given by experts, thus the decision method based on PHFS is more true and reliable. In this paper, multi-attribute decision-making (MADM) method is proposed under probabilistic hesitant fuzzy environment, which is based the new distance measures of probabilistic hesitant fuzzy elements (PHFEs) and the COmplex PRoportional ASsessment (COPRAS) method. Firstly, the existing problems of some distances are analyzed and we propose some new distance measures including new Hamming distance, new Euclidean distance and new generalized distance under probabilistic hesitant fuzzy environment. Secondly, a maximizing deviation method based on the new Hamming distance measure is proposed to obtain the attribute weights in probabilistic hesitant fuzzy information. Then, the COPRAS method is extended to solve MADM problems under probabilistic hesitant fuzzy environment. Finally, compared other methods, an example is given to demonstrate the effectiveness of the proposed method.

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Section: Proof (1)nonnegativementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Multi-Attribute Decision-Making Method Based Distance and COPRAS Method with Probabilistic Hesitant Fuzzy Environment

Song¹,

Chen²

2021

IJCIS

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“…The proportion contained in PHF2TLTSs originates from statistic, which should be considered to render accurate decisions 57,76 . Accordingly, the score and deviation functions are defined as follows:…”

Section: Risk Attitude‐oriented Proportional Hesitant 2‐tuple Linguistic Pa Operatorsmentioning

confidence: 99%

Power‐average‐operator‐based hybrid multiattribute online product recommendation model for consumer decision‐making

et al. 2021

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This study develops a power‐average‐operator‐based hybrid multiattribute online product recommendation model that considers the consumer's risk attitude to rank categoric product options as a complement to existing recommender systems. Online production recommendation plays a key role in the development of e‐commerce, and can greatly improve consumers' shopping experiences. However, few online shopping sites provide interactive decision aids for consumers such that they can articulate their preferences towards multiple selection attributes with the purpose of mitigating choice difficulty and improving decision quality. Additionally, consumers' risk attitudes to online shopping dramatically impact their product choices. In the model proposed in this paper, the risk attitude‐based power average (RAPA) operator is used to integrate the risk attitude of the decision‐maker into the information fusion process of multiple attribute decision‐making. Subsequently, the risk attitude function, with several basic types, is introduced to quantify the risk attitude of the decision‐maker for use in the RAPA operator. A proportional hesitant fuzzy 2‐tuple linguistic term set (PHF2TLTS) is constructed by incorporating a binary of linguistic information aiming to comprehensively analyze the hybrid product information. With a focus on the information fusion process, the proportional hesitant 2‐tuple linguistic RAPA operator and weighted proportional hesitant 2‐tuple linguistic RAPA operator are introduced to aggregate a given set of PHF2TLTSs. The validity of the proposed model is demonstrated using an illustrative example, a comparison with existing approaches and detailed explanations of the performance differences.

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“…Herrera and Martínez 13 developed a model using linguistic FSs to deal with multigranular hierarchical linguistic concepts. Chen et al 14 presented a fuzzy‐based linguistic approach in large‐scale group decision‐making context.…”

Section: Introductionmentioning

confidence: 99%

Linguistic Einstein aggregation operator‐based TOPSIS for multicriteria group decision making in linguistic Pythagorean fuzzy environment

Sarkar¹,

Biswas

2021

Int J Intell Syst

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This article presents a new family of linguistic Pythagorean fuzzy aggregation operations based on Einstein t‐norms and t‐conorms. Some of their necessary properties are also discussed. In the proposed method, a generalized weighted distance measure is developed using a linguistic‐scale function to evaluate differences among linguistic Pythagorean fuzzy sets (LPFSs). An entropy measure is also introduced for LPFS to measure fuzziness associated with linguistic decision information. Moreover, a technique for ordering preference by similarity to ideal solution (TOPSIS)‐based methodology is constructed through the newly defined concepts to address linguistic Pythagorean fuzzy multicriteria group decision‐making problems, where the information about weight is either completely known or unknown. Subsequently, weights of decision makers are computed through a TOPSIS‐based algorithm, and weights of criteria are evaluated by introducing a linguistic Pythagorean fuzzy entropy weight model. To minimize information loss throughout the decision‐making procedure, aggregation is done at the final stage for obtaining the final ranking of alternatives. Finally, several practical examples are considered, solved, and compared with existing methods to exhibit the robustness of the proposed methodology. Also, a sensitivity analysis is performed to establish the dynamic nature of the proposed model.

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Identifying and prioritizing factors affecting in-cabin passenger comfort on high-speed rail in China: A fuzzy-based linguistic approach

Cited by 59 publications

References 77 publications

Multi-Attribute Decision-Making Method Based Distance and COPRAS Method with Probabilistic Hesitant Fuzzy Environment

Multi-Attribute Decision-Making Method Based Distance and COPRAS Method with Probabilistic Hesitant Fuzzy Environment

Power‐average‐operator‐based hybrid multiattribute online product recommendation model for consumer decision‐making

Linguistic Einstein aggregation operator‐based TOPSIS for multicriteria group decision making in linguistic Pythagorean fuzzy environment

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