Article
Automation & Control Systems
Yuxin Zhao, Nan Jiang, Xiong Deng
Summary: In this article, a new DM approach based on Wasserstein distance is proposed for HFLTSs in qualitative decision making. Weighted and ordered weighted versions of HFLTSs are derived, and the proposed measures are shown to be rational and efficient in practical applications.
IEEE TRANSACTIONS ON CYBERNETICS
(2022)
Article
Computer Science, Artificial Intelligence
Lili Rong, Lei Wang, Peide Liu, Baoying Zhu
Summary: This paper introduces a new evaluation method for MOOCs based on multi-attribute group decision-making, which proves to be effective and superior in the evaluation of MOOCs through the construction of evaluation index system and the development of aggregation operators. It provides reference and suggestions for the improvement of MOOCs.
INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS
(2021)
Article
Computer Science, Artificial Intelligence
Xinli You, Fujun Hou
Summary: The DEMATEL method is effective for identifying key elements and causal relationships in complex systems. This study proposes enhancements by using multigranular hesitant fuzzy linguistic term sets for expert evaluation, establishing expert weight model based on similarity and entropy of HFLTSs, and utilizing a consensus reach process to obtain a satisfactory group solution.
INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS
(2021)
Article
Computer Science, Interdisciplinary Applications
Huimin Zhang, Yiyi Dai
Summary: This paper introduces new distance and entropy measures for hesitant fuzzy linguistic term sets (HFLTSs) and hesitant fuzzy linguistic preference relations (HFLPRs) and proposes an information aggregation method and two consensus improvement models for group decision making (GDM). The first model is a four-stage optimization model, based on which the revised individual and collective opinions can be obtained. The results demonstrate that the proposed models can better deal with the issues in existing consensus models.
COMPUTERS & INDUSTRIAL ENGINEERING
(2023)
Article
Operations Research & Management Science
Wenyu Yu, Zhen Zhang, Qiuyan Zhong
Summary: A novel consensus model based on multi-granular HFLTSs is proposed in this paper, aiming to help decision makers reach consensus in multi-attribute group decision making. The model defines a consensus measure and an optimization model to minimize decision makers' preference adjustment, with numerical results demonstrating its characteristics.
ANNALS OF OPERATIONS RESEARCH
(2021)
Article
Computer Science, Artificial Intelligence
Meng Zhao, Yiqi Hu, Song Wu, Zeshui Xu
Summary: Teleconsultation is important for the rational use of health resources and the implementation of hierarchical diagnosis and treatment. This article proposes a mathematical model for teleconsultation decision support system, taking into account the differences in responsibilities between remote experts and attending physicians. The proposed methods are applied to a sinusitis teleconsultation case to demonstrate their effectiveness.
IEEE TRANSACTIONS ON FUZZY SYSTEMS
(2023)
Article
Computer Science, Interdisciplinary Applications
Rosa M. Rodriguez, Alvaro Labella, Mikel Sesma-Sara, Humberto Bustince, Luis Martinez
Summary: Large-scale group decision-making under uncertainty has attracted interest recently due to its necessity and challenges. Consensus Reaching Processes (CRPs) have been applied to address scalability issues, with a new cohesion measure introduced to reduce the impact of internal disagreements in majority-driven CRPs.
COMPUTERS & INDUSTRIAL ENGINEERING
(2021)
Article
Computer Science, Artificial Intelligence
Lili Rong, Lei Wang, Peide Liu
Summary: The study addresses the primary issue of selecting and evaluating fresh food suppliers for supermarkets through a novel decision-making method. A new evaluation index is constructed and the effectiveness and superiority of the proposed method are compared with other approaches.
INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS
(2022)
Article
Computer Science, Interdisciplinary Applications
Quanyu Ding, Ying-Ming Wang, Mark Goh, Rosa M. Rodriguez, Luis Martinez
Summary: Real-world decision-making problems are often defined under uncertain contexts. To overcome these problems, this paper introduces a new decision-making model that considers the psychological behavior of decision makers and facilitates preference modeling under uncertainty.
COMPUTERS & INDUSTRIAL ENGINEERING
(2022)
Article
Physics, Multidisciplinary
Shuangsheng Wu, Jie Lin, Zhenyu Zhang
Summary: The paper analyzes the existing distance measures between hesitant fuzzy linguistic term sets (HFLTSs) and proposes improved measures that consider more factors, satisfying basic properties and avoiding information loss.
Article
Computer Science, Artificial Intelligence
Mingwei Lin, Zheyu Chen, Riqing Chen, Hamido Fujita
Summary: The study introduces a novel hesitant fuzzy linguistic decision-making method to evaluate startup companies. By using the proposed method, all alternatives can be ranked and nonoptimal alternatives can be improved.
INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS
(2021)
Article
Computer Science, Artificial Intelligence
Tanya Malhotra, Anjana Gupta
Summary: This article proposes a method to deal with unbalanced linguistic terms by using a specific algorithm and a 2-tuple model, aiming to assist experts in addressing difficulties in problem evaluation.
IEEE TRANSACTIONS ON FUZZY SYSTEMS
(2021)
Review
Mathematics
Francisco Rodrigues Lima-Junior, Mery Ellen Brandt de Oliveira, Carlos Henrique Lopes Resende
Summary: Supply chain management involves various decision-making problems that affect business and supply chain performance. Studies have emerged recently that apply techniques based on Hesitant Fuzzy Linguistic Term Sets (HFLTSs) and their extensions in SCM. This study presents a systematic review of these applications, providing an overview, highlighting trends, and identifying research opportunities. The results show that supplier selection, failure evaluation, and performance evaluation are common problems, and the automotive sector is predominant in the analyzed studies. The study contributes to the development of new studies involving HFLTSs and their extensions in decision-making problems.
Article
Computer Science, Artificial Intelligence
Sidong Xian, Danni Ma, Xu Feng
Summary: This study proposes a multi-criteria decision-making model based on a new fuzzy set, which can better solve complex decision problems and provides a new way to solve them.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Computer Science, Interdisciplinary Applications
Yaya Liu, Rosa M. Rodriguez, Jindong Qin, Luis Martinez
Summary: This study introduces a novel MCGDM method which reduces information loss in preference aggregation process by utilizing extended hesitant fuzzy linguistic term sets (EHFLTS). It also proposes new type 1 and type 2 fuzzy envelopes to enhance the flexibility of computation process.
COMPUTERS & INDUSTRIAL ENGINEERING
(2022)
Article
Hospitality, Leisure, Sport & Tourism
Zhang-Peng Tian, He-Ming Liang, Ru-Xin Nie, Jian-Qiang Wang
Summary: This study develops an integrated multi-criteria group decision-making method for evaluating low-carbon tourism attractions, which includes the best-worst method, the extended relative entropy-based method, and the multi-granular linguistic distribution ORESTE method.
CURRENT ISSUES IN TOURISM
(2022)
Article
Management
Weimin Ma, Kaixin Gong, Zhangpeng Tian
Summary: Under the mainstream development trend of energy conservation, environmental protection, and sustainability, green supplier selection has become of great importance. This article proposes a new heterogeneous large-scale group decision-making method based on subgroup leaders, and demonstrates its applicability and effectiveness through an example.
JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY
(2023)
Article
Computer Science, Artificial Intelligence
Ru-xin Nie, Zhang-peng Tian, Ru-yin Long, Wei Dong
Summary: With the rapid growth of population and industrialization, household electricity demand (HED) has become a crucial aspect of energy demand. This paper proposes a time series-based HED forecasting method, which includes data pre-processing, feature selection, and forecasting phases, taking into account various factors influencing HED.
EXPERT SYSTEMS WITH APPLICATIONS
(2022)
Article
Computer Science, Information Systems
Honggang Peng, Zhi Xiao, Xiaokang Wang, Jianqiang Wang, Jian Li
Summary: This paper aims to explore Z-number outranking theories and the corresponding MCDM method based on the idea of ELECTRE III. The concordance and discordance indices of Z-numbers are defined by processing their bimodal uncertainty fully. Three types of novel outranking relations for Z-numbers are presented by comparing these indices systematically. An extended MCDM method with the distillation and flow ranking rules is proposed to detect outranking relations among alternatives under multiple criteria.
INFORMATION SCIENCES
(2023)
Article
Hospitality, Leisure, Sport & Tourism
Ru-xin Nie, Kwai-sang Chin, Zhang-peng Tian, Jian-qiang Wang, Hong-yu Zhang
Summary: This paper explores the effects of COVID-19 pandemic on dynamic classification of service quality attributes and proposes improvement strategies based on evidence from online reviews. The study reveals the dynamics of service quality attributes for different customer segments and their impact on customer satisfaction. It contributes to hospitality marketing and crisis management by quantifying the dynamics of service quality and providing practical implications.
INTERNATIONAL JOURNAL OF CONTEMPORARY HOSPITALITY MANAGEMENT
(2023)
Article
Computer Science, Interdisciplinary Applications
Zhang-peng Tian, He-ming Liang, Ru-xin Nie, Xiao-kang Wang, Jian-qiang Wang
Summary: This paper proposes a sentiment analysis-based multi-criteria decision-making method to help consumers make EV purchase choices. The sentiment analysis results are transformed into hesitant intuitionistic fuzzy elements to derive the group opinion for each alternative. A comprehensive weighting method is developed to determine the weights of criteria. The ranking of candidate EV series can be obtained through the extended ORESTE method based on hesitant intuitionistic fuzzy Chebyshev distance. The results of sentiment analysis can also be useful for companies to explore consumers' demand for EVs.
COMPUTERS & INDUSTRIAL ENGINEERING
(2023)
Article
Biochemistry & Molecular Biology
Zhe Chen, Xiaolu Qu, Chungang Feng, Binbin Guo, Huanxi Zhu, Leyan Yan
Summary: The influence of monochromatic green light on hatching performance and embryo development in geese was investigated. The involvement of the liver in green light transduction and its underlying molecular mechanisms were also studied. The results showed that green light promoted embryonic development and hatching performance, with effects on myogenic regulatory factors and energy metabolism in the liver and muscle.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2023)
Article
Computer Science, Artificial Intelligence
Zi-yu Chen, Fei Xiao, Xiao-kang Wang, Wen-hui Hou, Rui-lu Huang, Jian-qiang Wang
Summary: The incidence and mortality of lung cancer in China are high, and misdiagnosis and missed diagnosis are common due to limited professional technology. To improve diagnosis accuracy, this paper proposes an interpretable diagnostic method based on Chinese electronic medical records (EMRs). The method achieves excellent results in lung cancer diagnosis, outperforming existing methods in terms of precision, recall, F1 score, AUROC, and AUPRC.
Article
Automation & Control Systems
Xiao-Kang Wang, Min-hui Deng, Wen hui Hou, Lang He, Fei Qu, Jian-Qiang Wang
Summary: This study modifies the evidential reasoning (ER) algorithm with linguistic correlation and applies it to multiple attribute group decision-making (MAGDM) problems within probabilistic linguistic terms sets (PLTSs). The correlations between different linguistic terms are defined and integrated into the original ER to reduce contradiction caused by expressive preferences. Moreover, linguistic correlation is involved in the calculation of reliability to adjust the distance measure, reducing unreliability caused by decision-makers' preferences.
INTERNATIONAL JOURNAL OF FUZZY SYSTEMS
(2023)
Review
Management
Zi-yu Chen, Fei Xiao, Yi-ting Wang, Ya-nan Wang, Wen-hui Hou, Jian-qiang Wang, Lin Li
Summary: The online reviews provided by patients contain various aspects of patient satisfaction. However, analyzing these reviews accurately is difficult due to the lack of constraints on patient expression. To address this issue, a multi-criteria decision-making method based on online review analysis is proposed.
JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY
(2023)
Article
Mathematics
Zhiping Hou, Sangsang He, Ruxia Liang, Junbo Li, Ruilu Huang, Jianqiang Wang
Summary: Evaluation of hotel website service quality has received extensive attention, but previous studies have overlooked human hesitance and uncertainty in judgments, as well as the simultaneous consideration of hotel managers and customers' psychological behaviors. This study explores criteria for evaluating the service quality of economy hotel websites and proposes a hybrid evaluation model to address hesitation and uncertainty. The model utilizes probabilistic linguistic term sets to capture qualitative assessments and applies analytical network process to prioritize website features. It further integrates the TODIM-PROMETHEE II method to rank alternatives considering psychological factors. The effectiveness of the model is illustrated through a case study of economy hotel websites in China, highlighting service competence and customer relationship as the most important performance features. Conclusions and implications are derived from the results.
