Jianming Zhan

Prof. Jianming Zhan

Department of Mathematics, Hubei University for Nationalities, Enshi 445000, Hubei, China
orcid

Research Focus & Metrics

Academic Career Length

27Years (2000-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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7 July 2020 in IEEE Transactions on Fuzzy Systems
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Journal Article
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JZJianming Zhan
Jianming Zhan
HJHaibo Jiang
Haibo Jiang
YYYiyu Yao
Yiyu Yao
In contrast to two-way decisions (2WD), three-way decisions (3WD) can effectively reduce decision risks by utilizing a new delayed decision option. This paper incorporates 3WD into multi-attribute decision-making (MADM) based on an outranking relation. We construct the outranked set for each alternative and introduce a hybrid information table that combines an MADM matrix with a loss function table. We propose three strategies to design a new 3WD model for MADM. The rationality and effectiveness of the proposed 3WD method are demonstrated by solving a problem of enterprise project investment (EPI) target selections. Finally, we provide the comparative analysis and two experimental evaluations. The results show that the proposed 3WD method is effective and practically useful.

1 February 2019 in Information Sciences
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Journal Article
Closed access
JZJianming Zhan
Jianming Zhan
BSBingzhen Sun
Bingzhen Sun
José Carlos AlcantudJosé Carlos Alcantud
José Carlos Alcantud

18 June 2016 in Artificial Intelligence Review
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Journal Article
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XMXueling Ma
Xueling Ma
QLQi Liu
Qi Liu
JZJianming Zhan
Jianming Zhan

7 May 2021 in IEEE Transactions on Fuzzy Systems
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Journal Article
Closed access
JZJianming Zhan
Jianming Zhan
JYJin Ye
Jin Ye
Weiping DingWeiping Ding
Weiping Ding
PLPeide Liu
Peide Liu
The existing three-way decision (TWD)-making methods cannot effectively handle incomplete multiattribute decision-making (MADM) problems in real life; it is necessary to explore an effective three-way MADM model in incomplete fuzzy decision systems (IFDSs). First, we consider the preference of decision makers for each alternative and introduce the concept of predecisions, thus an IFDS is obtained. Then, the weighted conditional probabilities are calculated with the aid of the defined similarity relation. Subsequently, we introduce the notion of relative utility functions and then present an approach to determine the relative utility function values. Afterward, we construct a TWD model in IFDSs and apply it to the modeling of incomplete MADM (IMADM) problems. Our study not only enriches TWD and MADM theories but also provides a new perspective for realistic IMADM problems. At last, the results of comparative and experimental analyses demonstrate the validity, stability, and superiority of our proposed model.

1 July 2017 in Applied Soft Computing
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Journal Article
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JZJianming Zhan
Jianming Zhan
MAMuhammad Irfan Ali
Muhammad Irfan Ali
NMNayyar Mehmood
Nayyar Mehmood

1 May 2017 in Applied Soft Computing
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Journal Article
Closed access
JZJianming Zhan
Jianming Zhan
QLQi Liu
Qi Liu
Tutut HerawanTutut Herawan
Tutut Herawan