Probabilistic linguistic information fusion: A survey on aggregation operators in terms of principles, definitions, classifications, applications, and challenges

Mi, Xiaomei; Liao, Huchang; Wu, Xin; Zhang, Xu

doi:10.1002/int.22216

Cited by 55 publications

(30 citation statements)

References 61 publications

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“…Remark 1. As reviewed in Mi et al (2020), up to now existing operations of PLTSs can be divided into five types: symbolic-based computation (Pang et al, 2016), semantic-based computation (Gou and Xu, 2016;Wu and Liao, 2019), triangular norms-based computation (Klement et al, 2000), evidence reasoning-based computation (Li and Wei, 2019) and double alpha-cut-based computation (Jiang and Liao, 2020). Among these operations, only the semantic-based computation (Gou and Xu, 2016;Wu and Liao, 2019) and the evidence reasoning-based computation (Li and Wei, 2019) satisfy the closure of operation of PLTSs.…”

Section: Aggregation Operators Of Pltssmentioning

confidence: 99%

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An Entropy-Based Method for Probabilistic Linguistic Group Decision Making and its Application of Selecting Car Sharing Platforms

Xu¹,

Wan²,

Dong³

2020

Informatica

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As the tourism and mobile internet develop, car sharing is becoming more and more popular. How to select an appropriate car sharing platform is an important issue to tourists. The car sharing platform selection can be regarded as a kind of multi-attribute group decision making (MAGDM) problems. The probabilistic linguistic term set (PLTS) is a powerful tool to express tourists' evaluations in the car sharing platform selection. This paper develops a probabilistic linguistic group decision making method for selecting a suitable car sharing platform. First, two aggregation operators of PLTSs are proposed. Subsequently, a fuzzy entropy and a hesitancy entropy of a PLTS are developed to measure the fuzziness and hesitancy of a PLTS, respectively. Combining the fuzzy entropy and hesitancy entropy, a total entropy of a PLTS is generated. Furthermore, a cross entropy between PLTSs is proposed as well. Using the total entropy and cross entropy, DMs' weights and attribute weights are determined, respectively. By defining preference functions with PLTSs, an improved PL-PROMETHEE approach is developed to rank alternatives. Thereby, a novel method is proposed for solving MAGDM with PLTSs. A car sharing platform selection is examined at length to show the application and superiority of the proposed method.

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Section: Aggregation Operators Of Pltssmentioning

confidence: 99%

“…Recently, diverse types of operators, such as power operators and dependent weighted average operators , have been proposed one after another. Furthermore, Mi et al (2020) conducted a survey of existing achievements on operations of PLTSs and aggregation operators.…”

Section: Introductionmentioning

confidence: 99%

An Entropy-Based Method for Probabilistic Linguistic Group Decision Making and its Application of Selecting Car Sharing Platforms

Xu¹,

Wan²,

Dong³

2020

Informatica

View full text Add to dashboard Cite

show abstract

“…Especially, the PLTS proposed by Pang et al (2016) has been regarded as a flexible technique to depict both fuzzy uncertainty and probabilistic uncertainty existed in comprehensive decision-making problems. Many achievements and fruitful results have been obtained over the past several years in terms of decision-making and information fusion (Liao et al 2020;Mi et al 2020). However, currently, as far as we know, there is no research focused on the UTASTAR method with probabilistic linguistic information.…”

Section: Introductionmentioning

confidence: 99%

Battery Supplier Development for New Energy Vehicles by a Probabilistic Linguistic Utastar Method

et al. 2021

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New energy vehicles can improve the environmental pollution and thus benefit people’s healthy life. As a core component of new energy vehicles, batteries play a crucial role in the performance of new energy vehicles. There are many factors to be considered when selecting the battery for a new energy vehicle, so it can be regarded as a MCDM problem. This study builds a useful model by combining the PLTS with the UTASTAR method. Firstly, to represent the uncertain and fuzzy information of experts, we use the PLTSs to accurately express the linguistic information of experts. Given that the weights of criteria are often different and there are some preferences for criteria among experts, we use the BWM to determine the weights of criteria, which can deal with hesitant information and make the result suitable for experts’ preferences. The method proposed in this study can sort all alternatives based on a small amount of data. To show its applicability, we implement the method in the selection of new energy vehicle battery suppliers. Comparative analysis and discussions are made to verify the effectiveness of the method.

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“…Yi and Li 10 developed the induced cluster‐based ordered weighted averaging operator for the distributed structural characteristics of arguments. Some other state‐of‐the‐art developments in this area refer to Reference [11].…”

Section: Introductionmentioning

confidence: 99%

On investigation of the Bayesian anomaly in multiple imprecise dependent information aggregation for system reliability evaluation

et al. 2021

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The increasing complexity of the modern engineering system has made the multisource information fusion a necessary yet challenging task. In the context of reliability engineering, the information fusion process is either ineffective or less efficient as the aggregation error increases with respect to the collection of multiple dependent pieces of evidence. To address this challenge, this paper proposes a comprehensive Bayesian approach for system reliability evaluation that considers multiple, dependent sources of information. We show that the so‐called “Bayesian anomaly,” a type of aggregation error, is caused by misuse of the dependent information and could be eliminated if all available information is properly addressed. A topological technique is employed as a tool for information fusion in the likelihood construction. A likelihood‐based approach is then developed to formulate the overall likelihood as well as the reliability model. These two techniques are embedded into a comprehensive Bayesian framework to allow for an efficient evaluation of the system reliability. Our approach has also been extended to include imprecise information, such as interval and/or censored data, which is more frequently encountered in practical engineering. We demonstrate the proposed method through several numerical cases and one real‐life application example. This study provides a better understanding of the role of dependent information in system reliability evaluation. In addition, it presents an efficient pathway to extract the inherent dependency information embedded in imperfect data sets.

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Probabilistic linguistic information fusion: A survey on aggregation operators in terms of principles, definitions, classifications, applications, and challenges

Cited by 55 publications

References 61 publications

An Entropy-Based Method for Probabilistic Linguistic Group Decision Making and its Application of Selecting Car Sharing Platforms

An Entropy-Based Method for Probabilistic Linguistic Group Decision Making and its Application of Selecting Car Sharing Platforms

Battery Supplier Development for New Energy Vehicles by a Probabilistic Linguistic Utastar Method

On investigation of the Bayesian anomaly in multiple imprecise dependent information aggregation for system reliability evaluation

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