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Ming Tang
Business School, Sichuan University, Chengdu 610064, China

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Journal article
Published: 15 April 2021 in IEEE Transactions on Systems, Man, and Cybernetics: Systems
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The widespread utilization of novel technological and societal paradigms gave birth to the development large-scale group decision making. This study focuses on two issues regarding the structure of the large group. The first is about the overlapping clusters/communities (interdependent subgroups) of large-scale experts identified from the dimension reduction process. The second is regarding the situation in which internal and external experts (i.e., heterogeneous experts) exist in a large-scale group decision-making problem simultaneously. To manage the first issue, we propose to use an existing overlapping community detection method to cluster experts considering the independencies of communities. To address the second issue, a delegation mechanism is introduced to allocate the trust weights of external experts to internal experts. Furthermore, to reach a consensus for large-scale experts, a consensus measure based on two reference points (global collective preference and community preference) is given. Finally, an illustrative example regarding 5G technology investment is provided to verify the applicability of the proposed model.

ACS Style

Ming Tang; Huchang Liao; Hamido Fujita. Delegation Mechanism-Based Large-Scale Group Decision Making With Heterogeneous Experts and Overlapping Communities. IEEE Transactions on Systems, Man, and Cybernetics: Systems 2021, PP, 1 -14.

AMA Style

Ming Tang, Huchang Liao, Hamido Fujita. Delegation Mechanism-Based Large-Scale Group Decision Making With Heterogeneous Experts and Overlapping Communities. IEEE Transactions on Systems, Man, and Cybernetics: Systems. 2021; PP (99):1-14.

Chicago/Turabian Style

Ming Tang; Huchang Liao; Hamido Fujita. 2021. "Delegation Mechanism-Based Large-Scale Group Decision Making With Heterogeneous Experts and Overlapping Communities." IEEE Transactions on Systems, Man, and Cybernetics: Systems PP, no. 99: 1-14.

Journal article
Published: 13 March 2021 in Information Sciences
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With the increasing popularity of Pharmaceutical Industry 4.0, products and services provided by suppliers play a significantly important role for a pharmaceutical enterprise. To evaluate the performance of suppliers comprehensively regarding multiple criteria, it is necessary to invite inside managers from the enterprise and outside consultants with expertise to form a decision-making committee. Within this context, this study proposes a multi-attribute group decision making model for pharmaceutical supplier selection with internal and external (heterogeneous) experts. Considering the complexity of the decision-making environment, we suppose that the experts use triangular fuzzy numbers to express their imprecise information. We identify two kinds of conflicts among experts, and introduce a conflict resolution process with a feedback mechanism. In the feedback mechanism, two non-cooperative behavior management approaches are introduced corresponding to the two kinds of experts. Afterwards, an algorithm for multiple-attribute group decision making with triangular fuzzy numbers and heterogeneous experts is presented. Finally, an illustrative example about pharmaceutical supplier selection is provided to verify the feasibility of the proposed method and some managerial insights are given.

ACS Style

Huchang Liao; Lisi Kuang; Yuxi Liu; Ming Tang. Non-cooperative behavior management in group decision making by a conflict resolution process and its implementation for pharmaceutical supplier selection. Information Sciences 2021, 567, 131 -145.

AMA Style

Huchang Liao, Lisi Kuang, Yuxi Liu, Ming Tang. Non-cooperative behavior management in group decision making by a conflict resolution process and its implementation for pharmaceutical supplier selection. Information Sciences. 2021; 567 ():131-145.

Chicago/Turabian Style

Huchang Liao; Lisi Kuang; Yuxi Liu; Ming Tang. 2021. "Non-cooperative behavior management in group decision making by a conflict resolution process and its implementation for pharmaceutical supplier selection." Information Sciences 567, no. : 131-145.

Original article
Published: 23 December 2020 in Expert Systems
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Social network analysis is an efficient tool to investigate the relationships of decision‐makers in large‐scale group decision making (LSGDM). Existing social network‐based LSGDM studies generally assumed that each decision‐maker has a single role or belongs to only one subgroup. The assumption that a decision‐maker has multiple roles or belongs to multiple subgroups is rarely taken into consideration. In this regard, this study proposes an overlap graph model (OGM) in which decision‐makers can participate in the decision‐making process in multiple roles to solve LSGDM problems with social trust information. In the OGM, decision‐makers are firstly divided into two types: multiple‐role decision‐makers and single‐role decision‐makers. Since it is unpractical for a decision‐maker to evaluate all others in a LSGDM problem, we then investigate how to construct a complete social trust network based on an Agent mechanism. A two‐stage consensus reaching process is proposed to reduce the discrepancies among decision‐makers: The first stage is for single‐role decision‐makers within a subgroup while the second stage is for Agents and multiple‐role decision‐makers. Finally, an illustrative example regarding selecting treatment plans for critical patients in COVID‐19 is provided to test the applicability and rationality of the proposed model.

ACS Style

Huchang Liao; Runzhi Tan; Ming Tang. An overlap graph model for large‐scale group decision making with social trust information considering the multiple roles of experts. Expert Systems 2020, 1 .

AMA Style

Huchang Liao, Runzhi Tan, Ming Tang. An overlap graph model for large‐scale group decision making with social trust information considering the multiple roles of experts. Expert Systems. 2020; ():1.

Chicago/Turabian Style

Huchang Liao; Runzhi Tan; Ming Tang. 2020. "An overlap graph model for large‐scale group decision making with social trust information considering the multiple roles of experts." Expert Systems , no. : 1.

Journal article
Published: 03 November 2020 in Journal of the Operational Research Society
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ACS Style

Ming Tang; Huchang Liao; Gang Kou. Type α and type γ consensus for multi-stage emergency group decision making based on mining consensus sequences. Journal of the Operational Research Society 2020, 1 -17.

AMA Style

Ming Tang, Huchang Liao, Gang Kou. Type α and type γ consensus for multi-stage emergency group decision making based on mining consensus sequences. Journal of the Operational Research Society. 2020; ():1-17.

Chicago/Turabian Style

Ming Tang; Huchang Liao; Gang Kou. 2020. "Type α and type γ consensus for multi-stage emergency group decision making based on mining consensus sequences." Journal of the Operational Research Society , no. : 1-17.

Articles
Published: 13 May 2020 in Journal of the Operational Research Society
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With the increasing complexity of decision-making environment and the development of societal demands, large-scale group decision making (LSGDM) has become a hot topic in recent years. Due to the demand of the current decision-making environment, up to now, studies regarding LSGDM methods focussing on different approaches have been published. However, there are few studies that focus on evaluating the results of LSGDM problems. This study proposes three subgroup quality indices, namely, consistency degree, nearness degree and evenness degree, to measure the effectiveness of LSGDM methods. These three quality indices not only can evaluate the effect of a subgroup on the global group, but also can measure the effect of final decision results. Furthermore, the consistency measure is used to design the weights of subgroups, based on which an adaptive dynamic consensus reaching process is introduced. An illustrative example is given to verify the applicability and effectiveness of our proposed model.

ACS Style

Ming Tang; Huchang Liao; Xiaomei Mi; Xuanhua Xu; Francisco Herrera. Dynamic subgroup-quality-based consensus in managing consistency, nearness, and evenness quality indices for large-scale group decision making under hesitant environment. Journal of the Operational Research Society 2020, 72, 865 -878.

AMA Style

Ming Tang, Huchang Liao, Xiaomei Mi, Xuanhua Xu, Francisco Herrera. Dynamic subgroup-quality-based consensus in managing consistency, nearness, and evenness quality indices for large-scale group decision making under hesitant environment. Journal of the Operational Research Society. 2020; 72 (4):865-878.

Chicago/Turabian Style

Ming Tang; Huchang Liao; Xiaomei Mi; Xuanhua Xu; Francisco Herrera. 2020. "Dynamic subgroup-quality-based consensus in managing consistency, nearness, and evenness quality indices for large-scale group decision making under hesitant environment." Journal of the Operational Research Society 72, no. 4: 865-878.

Article
Published: 19 October 2019 in Cognitive Computation
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Hesitant fuzzy linguistic preference relations (HFLPRs) can be used to represent cognitive complex information in a situation in which people hesitate among several possible linguistic terms for the preference degrees of pairwise comparisons over alternatives. HFLPRs have attracted growing attention owing to their efficiency in dealing with increasingly cognitive complex decision-making problems. Due to the emergence of various studies on HFLPRs, it is necessary to make a comprehensive overview of the theory of HFLPRs and their applications. In this paper, we first review different types of linguistic representation models, including the hesitant fuzzy linguistic term set, hesitant 2-tuple fuzzy linguistic term set, probabilistic linguistic term set, and double-hierarchy hesitant fuzzy linguistic term set. The reasons for proposing these models are discussed in detail. Then, the hesitant linguistic preference relation models associated with the aforementioned linguistic representation models are addressed one by one. An overview is then provided in terms of their consistency properties, inconsistency-repairing processes, priority vector derivation methods, consensus measures, applications, and future directions. Basically, we try to answer to two questions: where we stand and what is next? The preference relations and consistency properties are discussed in detail. The inconsistency-repairing processes for those preference relations that are not acceptably consistent are summarized. Methods to derive the priorities from the HFLPRs and their extensions are further reviewed. The consensus measures and consensus-reaching processes for group decision making with HFLPRs and their extensions are discussed. The applications of HFLPRs and their extensions in different areas are highlighted. The future research directions regarding HFLPRs are given from different perspectives. This paper provides a comprehensive overview of the development and research status of HFLPRs for representing cognitive complex information. It can help researchers to identify the frontier of cognitive complex preference relation theory in the realm of decision analysis. Since the research on HFLPRs is still at its initial stage, this review has guiding significance for the later stage of study on this topic. Furthermore, this paper can engage further research or extend the research interests of scholars.

ACS Style

Huchang Liao; Ming Tang; Rui Qin; Xiaomei Mi; Abdulrahman Altalhi; Saleh Alshomrani; Francisco Herrera. Overview of Hesitant Linguistic Preference Relations for Representing Cognitive Complex Information: Where We Stand and What Is Next. Cognitive Computation 2019, 12, 25 -48.

AMA Style

Huchang Liao, Ming Tang, Rui Qin, Xiaomei Mi, Abdulrahman Altalhi, Saleh Alshomrani, Francisco Herrera. Overview of Hesitant Linguistic Preference Relations for Representing Cognitive Complex Information: Where We Stand and What Is Next. Cognitive Computation. 2019; 12 (1):25-48.

Chicago/Turabian Style

Huchang Liao; Ming Tang; Rui Qin; Xiaomei Mi; Abdulrahman Altalhi; Saleh Alshomrani; Francisco Herrera. 2019. "Overview of Hesitant Linguistic Preference Relations for Representing Cognitive Complex Information: Where We Stand and What Is Next." Cognitive Computation 12, no. 1: 25-48.

Research article
Published: 10 October 2019 in European Journal of Operational Research
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Large-scale group decision making, which involves dozens to hundreds of experts, is attracting increasing attention and has become an important topic in the field of decision making. Because of the clustering process, a large-scale group decision making problem can be divided into two levels: inter sub-group and intra sub-group. In existing consensus models under the large-scale group decision making environment, the degree of consensus within the intra sub-group is not truly taken into account. To deal with this issue, this work develops an adaptive consensus model for the sub-groups composed of hybrid strategies, with or without a feedback mechanism, according to the different levels of inter and intra degrees of consensus. These different levels of consensus are divided into four scenarios (high–high, high–low, low–high, low–low), and different feedback suggestions are generated corresponding to different cases. This hybrid mechanism can reduce the cost of supervision for the moderator. The fuzzy c-means clustering algorithm is used to classify experts. A weight-determining method combining the degree of cohesion and the size of a sub-group is introduced. Finally, an illustrative example is offered to verify the practicability of the proposed model. Some discussions and comparisons are provided to reveal the advantages and features of the proposed model.

ACS Style

Ming Tang; Huchang Liao; Jiuping Xu; Dalia Streimikiene; Xiaosong Zheng. Adaptive consensus reaching process with hybrid strategies for large-scale group decision making. European Journal of Operational Research 2019, 282, 957 -971.

AMA Style

Ming Tang, Huchang Liao, Jiuping Xu, Dalia Streimikiene, Xiaosong Zheng. Adaptive consensus reaching process with hybrid strategies for large-scale group decision making. European Journal of Operational Research. 2019; 282 (3):957-971.

Chicago/Turabian Style

Ming Tang; Huchang Liao; Jiuping Xu; Dalia Streimikiene; Xiaosong Zheng. 2019. "Adaptive consensus reaching process with hybrid strategies for large-scale group decision making." European Journal of Operational Research 282, no. 3: 957-971.

Journal article
Published: 01 October 2019 in Computers & Industrial Engineering
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ACS Style

Huchang Liao; Yilu Long; Ming Tang; Dalia Streimikiene; Benjamin Lev. Early lung cancer screening using double normalization-based multi-aggregation (DNMA) and Delphi methods with hesitant fuzzy information. Computers & Industrial Engineering 2019, 136, 453 -463.

AMA Style

Huchang Liao, Yilu Long, Ming Tang, Dalia Streimikiene, Benjamin Lev. Early lung cancer screening using double normalization-based multi-aggregation (DNMA) and Delphi methods with hesitant fuzzy information. Computers & Industrial Engineering. 2019; 136 ():453-463.

Chicago/Turabian Style

Huchang Liao; Yilu Long; Ming Tang; Dalia Streimikiene; Benjamin Lev. 2019. "Early lung cancer screening using double normalization-based multi-aggregation (DNMA) and Delphi methods with hesitant fuzzy information." Computers & Industrial Engineering 136, no. : 453-463.

Journal article
Published: 24 September 2019 in Knowledge-Based Systems
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The growth of global electricity demand has put forward higher requirements for power distribution networks. The high cost of the large-scale power system and the voice for the use of renewable energy impel the birth of the micro-grid which plays a complementary role in the power generation of large-scale power system. The construction of micro-grid planning is complex and many stakeholders’ opinions should be considered for a comprehensive evaluation. Furthermore, the development of social big data techniques, such as e-marketplace and e-democracy, makes experts have social relationships among them. This study aims to develop a consensus model to manage minority opinions for large-scale group decision making with social network analysis for micro-grid planning. To deal with the vague and uncertain features in complex micro-grid planning problems, experts are supposed to use hesitant fuzzy linguistic term sets to express their opinions. A social network analysis-based clustering method is introduced to classify experts. Besides, in a large-scale group decision making problem, the opinions of experts should be fully considered, especially the minority opinions. This model considers the minority opinions in a micro-grid planning problem and provides an approach to manage these opinions. Finally, we use an illustrative example concerning the micro-grid planning decision making in Ali district in Tibet to demonstrate the effectiveness and practicability of the proposed model.

ACS Style

Ruxue Ren; Ming Tang; Huchang Liao. Managing minority opinions in micro-grid planning by a social network analysis-based large scale group decision making method with hesitant fuzzy linguistic information. Knowledge-Based Systems 2019, 189, 105060 .

AMA Style

Ruxue Ren, Ming Tang, Huchang Liao. Managing minority opinions in micro-grid planning by a social network analysis-based large scale group decision making method with hesitant fuzzy linguistic information. Knowledge-Based Systems. 2019; 189 ():105060.

Chicago/Turabian Style

Ruxue Ren; Ming Tang; Huchang Liao. 2019. "Managing minority opinions in micro-grid planning by a social network analysis-based large scale group decision making method with hesitant fuzzy linguistic information." Knowledge-Based Systems 189, no. : 105060.

Journal article
Published: 18 June 2019 in Applied Soft Computing
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The probabilistic linguistic term set is a powerful tool to express and characterize people’s cognitive complex information and thus has obtained a great development in the last several years. To better use the probabilistic linguistic term sets in decision making, information measures such as the distance measure, similarity measure, entropy measure and correlation measure should be defined. However, as an important kind of information measure, the inclusion measure has not been defined by scholars. This study aims to propose the inclusion measure for probabilistic linguistic term sets. Formulas to calculate the inclusion degrees are put forward Then, we introduce the normalized axiomatic definitions of the distance, similarity and entropy measures of probabilistic linguistic term sets to construct a unified framework of information measures for probabilistic linguistic term sets. Based on these definitions, we present the relationships and transformation functions among the distance, similarity, entropy and inclusion measures. We believe that more formulas to calculate the distance, similarity, inclusion degree and entropy can be induced based on these transformation functions. Finally, we put forward an orthogonal clustering algorithm based on the inclusion measure and use it in classifying cities in the Economic Zone of Chengdu Plain, China.

ACS Style

Ming Tang; Yilu Long; Huchang Liao; Zeshui Xu. Inclusion measures of probabilistic linguistic term sets and their application in classifying cities in the Economic Zone of Chengdu Plain. Applied Soft Computing 2019, 82, 105572 .

AMA Style

Ming Tang, Yilu Long, Huchang Liao, Zeshui Xu. Inclusion measures of probabilistic linguistic term sets and their application in classifying cities in the Economic Zone of Chengdu Plain. Applied Soft Computing. 2019; 82 ():105572.

Chicago/Turabian Style

Ming Tang; Yilu Long; Huchang Liao; Zeshui Xu. 2019. "Inclusion measures of probabilistic linguistic term sets and their application in classifying cities in the Economic Zone of Chengdu Plain." Applied Soft Computing 82, no. : 105572.

Article
Published: 20 May 2019 in International Journal of Fuzzy Systems
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Hesitant fuzzy set, initiated 10 years ago, is an effective tool to deal with uncertain and vague information considering hesitancy when evaluating alternatives. It allows people to hesitate among several possible values for the membership degree to a given set. Hesitant fuzzy set has attracted a large number of researchers’ attention and has obtained great achievements up to now. Because of this expansion, we provide a comprehensive bibliometric overview on hesitant fuzzy sets with the objective of presenting a clear perspective to the field of hesitant fuzzy sets. A total of 484 publications retrieved from the core database of Web of Science are analyzed in detail. Many interesting results in terms of general statistics, top players with regard to country/region level, institute level, journal level, author level, highly cited papers and research topics are investigated. Two bibliometric software packages, VOSviewer and CiteSpace, help us to make visualization maps. It is hoped that our study can give insights into the historical context of HFSs and help researchers be aware of the significant advances in this field.

ACS Style

Huchang Liao; Ming Tang; Xinli Zhang; Abdullah Al-Barakati. Detecting and Visualizing in the Field of Hesitant Fuzzy Sets: A Bibliometric Analysis from 2009 to 2018. International Journal of Fuzzy Systems 2019, 21, 1289 -1305.

AMA Style

Huchang Liao, Ming Tang, Xinli Zhang, Abdullah Al-Barakati. Detecting and Visualizing in the Field of Hesitant Fuzzy Sets: A Bibliometric Analysis from 2009 to 2018. International Journal of Fuzzy Systems. 2019; 21 (5):1289-1305.

Chicago/Turabian Style

Huchang Liao; Ming Tang; Xinli Zhang; Abdullah Al-Barakati. 2019. "Detecting and Visualizing in the Field of Hesitant Fuzzy Sets: A Bibliometric Analysis from 2009 to 2018." International Journal of Fuzzy Systems 21, no. 5: 1289-1305.

Journal article
Published: 10 November 2018 in Omega
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The Essential Science Indicators (ESI) database is widely used to assess scientific outputs. The ESI database contains papers that entered the top 1% of sum citations in one discipline in the past ten years. Therefore, highly cited papers included in ESI database are of high quality in each field. This paper provides a bibliometric overview on the papers included in the ESI database in the field of operations research & management science. During the years of 2008 to 2017, there are 646 ESI highly cited papers in this area. Based on these 646 papers, we identify the most influential actors including journals, counties/regions, and institutes. The co-authorship relations among countries, institutes and authors characterize the collaboration status in the field of operations research and management science. The most cited papers are then presented. Finally, author keywords, keywords plus and words in title are analyzed, with hot research topics and future directions being provided.

ACS Style

Huchang Liao; Ming Tang; Zongmin Li; Benjamin Lev. Bibliometric analysis for highly cited papers in operations research and management science from 2008 to 2017 based on Essential Science Indicators. Omega 2018, 88, 223 -236.

AMA Style

Huchang Liao, Ming Tang, Zongmin Li, Benjamin Lev. Bibliometric analysis for highly cited papers in operations research and management science from 2008 to 2017 based on Essential Science Indicators. Omega. 2018; 88 ():223-236.

Chicago/Turabian Style

Huchang Liao; Ming Tang; Zongmin Li; Benjamin Lev. 2018. "Bibliometric analysis for highly cited papers in operations research and management science from 2008 to 2017 based on Essential Science Indicators." Omega 88, no. : 223-236.

Journal article
Published: 04 October 2018 in Information Fusion
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Recently, the Hesitant Fuzzy Linguistic Term Sets (HFLTSs) have been widely used to address cognitive complex linguistic information because of its advantage in representing vagueness and hesitation in qualitative decision-making process. Information measures, including distance measure, similarity measure, entropy measure, inclusion measure and correlation measure, are used to characterize the relationships between linguistic elements. Many decision-making theories are based on information measures. Up to now, distance, similarity, entropy and correlation measures have been proposed by scholars but there is no paper focuses on inclusion measure. This paper dedicates to filling this gap and the inclusion measure between HFLTSs are proposed. We discuss the relationships among distance, similarity, inclusion and entropy measures of HFLTSs. Given that clustering algorithm is an important application of information measures but there is few papers pay attention to clustering algorithm based on information measures in the environment of HFLTS, in this paper, we propose two clustering algorithms based on correlation measure and distance measure, respectively. After that, a case study concerning water resource bearing capacity is illustrated to verify the applicability of the proposed clustering algorithms.

ACS Style

Ming Tang; Huchang Liao. Managing information measures for hesitant fuzzy linguistic term sets and their applications in designing clustering algorithms. Information Fusion 2018, 50, 30 -42.

AMA Style

Ming Tang, Huchang Liao. Managing information measures for hesitant fuzzy linguistic term sets and their applications in designing clustering algorithms. Information Fusion. 2018; 50 ():30-42.

Chicago/Turabian Style

Ming Tang; Huchang Liao. 2018. "Managing information measures for hesitant fuzzy linguistic term sets and their applications in designing clustering algorithms." Information Fusion 50, no. : 30-42.

Journal article
Published: 21 May 2018 in Sustainability
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Sustainability (SUS) is a journal in the field of environmental, cultural, economic and social sustainability of human beings and civilization, which was founded in 2009. This paper provides a comprehensive bibliometric overview of the journal and 6459 publications from 2009 to 2018. In the paper, we first introduce the materials and methods used. Next, we provide the bibliometric results in four parts. In the first part, we present the publication structure and citation structure of SUS, including annual trends of publications and citations, sources that cite SUS publications, and the most highly cited papers in SUS. The primary influential countries and institutes as well as their co-authorship networks are illustrated in the second part. The co-citation networks of cited references, journals and authors are shown in the third part. Finally, the co-occurrence network of keywords and bursting citation keywords is detected. VOSviewer and CiteSpace software packages are used for graphical visualization.

ACS Style

Ming Tang; Huchang Liao; Zhengjun Wan; Enrique Herrera-Viedma; Marc A. Rosen. Ten Years of Sustainability (2009 to 2018): A Bibliometric Overview. Sustainability 2018, 10, 1655 .

AMA Style

Ming Tang, Huchang Liao, Zhengjun Wan, Enrique Herrera-Viedma, Marc A. Rosen. Ten Years of Sustainability (2009 to 2018): A Bibliometric Overview. Sustainability. 2018; 10 (5):1655.

Chicago/Turabian Style

Ming Tang; Huchang Liao; Zhengjun Wan; Enrique Herrera-Viedma; Marc A. Rosen. 2018. "Ten Years of Sustainability (2009 to 2018): A Bibliometric Overview." Sustainability 10, no. 5: 1655.

Journal article
Published: 13 April 2018 in International Journal of Environmental Research and Public Health
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Because the natural disaster system is a very comprehensive and large system, the disaster reduction scheme must rely on risk analysis. Experts’ knowledge and experiences play a critical role in disaster risk assessment. The hesitant fuzzy linguistic preference relation is an effective tool to express experts’ preference information when comparing pairwise alternatives. Owing to the lack of knowledge or a heavy workload, information may be missed in the hesitant fuzzy linguistic preference relation. Thus, an incomplete hesitant fuzzy linguistic preference relation is constructed. In this paper, we firstly discuss some properties of the additive consistent hesitant fuzzy linguistic preference relation. Next, the incomplete hesitant fuzzy linguistic preference relation, the normalized hesitant fuzzy linguistic preference relation, and the acceptable hesitant fuzzy linguistic preference relation are defined. Afterwards, three procedures to estimate the missing information are proposed. The first one deals with the situation in which there are only n−1 known judgments involving all the alternatives; the second one is used to estimate the missing information of the hesitant fuzzy linguistic preference relation with more known judgments; while the third procedure is used to deal with ignorance situations in which there is at least one alternative with totally missing information. Furthermore, an algorithm for group decision making with incomplete hesitant fuzzy linguistic preference relations is given. Finally, we illustrate our model with a case study about flood disaster risk evaluation. A comparative analysis is presented to testify the advantage of our method.

ACS Style

Ming Tang; Huchang Liao; Zongmin Li; Zeshui Xu. Nature Disaster Risk Evaluation with a Group Decision Making Method Based on Incomplete Hesitant Fuzzy Linguistic Preference Relations. International Journal of Environmental Research and Public Health 2018, 15, 751 .

AMA Style

Ming Tang, Huchang Liao, Zongmin Li, Zeshui Xu. Nature Disaster Risk Evaluation with a Group Decision Making Method Based on Incomplete Hesitant Fuzzy Linguistic Preference Relations. International Journal of Environmental Research and Public Health. 2018; 15 (4):751.

Chicago/Turabian Style

Ming Tang; Huchang Liao; Zongmin Li; Zeshui Xu. 2018. "Nature Disaster Risk Evaluation with a Group Decision Making Method Based on Incomplete Hesitant Fuzzy Linguistic Preference Relations." International Journal of Environmental Research and Public Health 15, no. 4: 751.

Journal article
Published: 11 January 2018 in Sustainability
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With the rapid development of “Internet plus”, medical care has entered the era of big data. However, there is little research on medical big data (MBD) from the perspectives of bibliometrics and visualization. The substantive research on the basic aspects of MBD itself is also rare. This study aims to explore the current status of medical big data through visualization analysis on the journal papers related to MBD. We analyze a total of 988 references which were downloaded from the Science Citation Index Expanded and the Social Science Citation Index databases from Web of Science and the time span was defined as “all years”. The GraphPad Prism 5, VOSviewer and CiteSpace softwares are used for analysis. Many results concerning the annual trends, the top players in terms of journal and institute levels, the citations and H-index in terms of country level, the keywords distribution, the highly cited papers, the co-authorship status and the most influential journals and authors are presented in this paper. This study points out the development status and trends on MBD. It can help people in the medical profession to get comprehensive understanding on the state of the art of MBD. It also has reference values for the research and application of the MBD visualization methods.

ACS Style

Huchang Liao; Ming Tang; Li Luo; Chunyang Li; Francisco Chiclana; Xiao-Jun Zeng. A Bibliometric Analysis and Visualization of Medical Big Data Research. Sustainability 2018, 10, 166 .

AMA Style

Huchang Liao, Ming Tang, Li Luo, Chunyang Li, Francisco Chiclana, Xiao-Jun Zeng. A Bibliometric Analysis and Visualization of Medical Big Data Research. Sustainability. 2018; 10 (2):166.

Chicago/Turabian Style

Huchang Liao; Ming Tang; Li Luo; Chunyang Li; Francisco Chiclana; Xiao-Jun Zeng. 2018. "A Bibliometric Analysis and Visualization of Medical Big Data Research." Sustainability 10, no. 2: 166.