Double Hierarchy Linguistic Term Set and Its Extensions

Gou, Xunjie; Zhang, Xu

doi:10.1007/978-3-030-51320-7_1

Cited by 5 publications

(1 citation statement)

References 33 publications

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“…Different types of grey fuzzy numbers have been developed such as grey hesitant fuzzy numbers (Liu et al , 2016) and intuitionistic grey numbers (Jiang et al , 2020). However, with regard to qualitative decision information like company performance and management ability, linguistic term is closer to people's cognition than the crisp numerical value (Gou and Xu, 2021). In view of this, the interval grey linguistic variables (Wang et al , 2019), three-parameter interval grey linguistic variables (Li and Yuan, 2017) and interval grey uncertain linguistic variables (Han et al , 2016a) are put forward successively, which simultaneously consider the linguistic evaluations of DMs and the uncertainty degree of decision information.…”

Section: Introducementioning

confidence: 99%

A novel consensus reaching method for MCGDM in social network with intuitionistic grey linguistic numbers

Guo

Li²,

Jing³

2022

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PurposeThe existing consensus reaching mechanisms ignore the influence of social triangle structure on the decision-makers’ (DMs') weights, and the consensus reaching process (CRP) fails to fully reflect the DMs' subjectivity and can be time consuming and costly. To solve these issues, a novel CRP for multi-criteria group decision-making (MCGDM) problems with intuitionistic grey linguistic numbers (IGLNs) is proposed in this paper.Design/methodology/approachFirst, a weight calculation method is proposed by analysing the triangle structure of DMs' social network and scale of adjacent nodes. Then, a consensus degree index based on three-level polygon area is defined and applied to identify the inconsistent DMs. Finally, the feedback mechanism based on particle swarm optimisation (PSO) algorithm under grey linguistic environment is developed, where subjective trust relationships in social network is utilised to determine the adjustment coefficient.FindingsThe advantages of the proposed method are highlighted by two practical applications of the evaluation of tunnel construction method and the selection of a hotel for the centralised isolation. Comparision analysis and numerical simulation are performed to reveal the effectiveness and applicability of the method.Practical implicationsThe proposed model can not only reflect the effect of triangle structure in social network on DMs' weights, but also reduce the time and cost of decision-making.Originality/valueThe main contribution of this paper is to propose a new MCGDM model based on intuitionistic grey linguistic numbers, which can handle the problem of inconsistency of information more effectively.

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Section: Introducementioning

confidence: 99%

A novel consensus reaching method for MCGDM in social network with intuitionistic grey linguistic numbers

Guo

Li²,

Jing³

2022

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Heterogeneous wireless network selection using feed forward double hierarchy linguistic neural network

Abdullah,

Ullah,

Ghani

2024

Artif Intell Rev

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Network selection in heterogeneous wireless networks (HWNs) is a complex issue that requires a thorough understanding of service features and user preferences. This is because the various wireless access technologies have varying capabilities and limitations, and the best network for a voice, video, and data service depends on a variety of factors. For selecting the optimal network in HWNs, varying factors such as the user’s position, accessible network resources, service quality requirements, and user preferences must be considered. The classical decision making procedure is very difficult and uncertain to select the desirable HWNs for voice, video, and data. Therefore, we develop a novel decision making model based on feed-forward neural networks under the double hierarchy linguistic information for the selection of the best HWNs for voice, video, and data. In this article, we introduce a novel feed-forward double hierarchy linguistic neural network using the Hamacher t-norm and t-conorm. Further, the feed-forward double hierarchy linguistic neural network applies to the decision making model for the selection of the best HWNs for voice, video, and data. In this novel decision making model, we first take the given data about HWNs and use the converting function to convert the given data into a double hierarchy linguistic term set. We calculate the hidden layer and output layer information by using Hamacher aggregation operations. Finally, we use the sigmoid activation function on the output layer information to decide on the best HWNs for voice, video, and data according to ranking. The proposed approach is compared with other existing models of decision making and the results of the comparison show that the proposed technique is applicable and reliable for the decision support model.

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Probabilistic Double Hierarchy Linguistic TOPSIS Method for MAGDM and Its Application to Teaching Quality Evaluation of College English

Wang

2022

Discrete Dynamics in Nature and Society

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College English is a compulsory course for college students. The teaching level of teachers in this course has naturally been evaluated by various schools. The teaching quality evaluation of college English is frequently viewed as a multiple attribute group decision-making (MAGDM) issue. The probabilistic double hierarchy linguistic not only conforms to people’s language expression habit of “adverb + adjective,” but can also accurately express its importance. Therefore, this paper comes up with the PDHL-TOPSIS mean for MAGDM based on the PDHLTS environment and applies it to the teaching quality evaluation of college English. On the one hand, we bring information entropy into the determination of target weight. The PDHL-TOPSIS technique is constructed and utilized for teaching level evaluation. Eventually, the PDHL-TOPSIS technique is compared with other decision-making means, and the novel mean turns out to be significant and valid.

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Double Hierarchy Linguistic Term Set and Its Extensions

Cited by 5 publications

References 33 publications

A novel consensus reaching method for MCGDM in social network with intuitionistic grey linguistic numbers

A novel consensus reaching method for MCGDM in social network with intuitionistic grey linguistic numbers

Heterogeneous wireless network selection using feed forward double hierarchy linguistic neural network

Probabilistic Double Hierarchy Linguistic TOPSIS Method for MAGDM and Its Application to Teaching Quality Evaluation of College English

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