Hong-yu Zhang

Hong-yu Zhang


Research Focus & Metrics

Academic Career Length

12Years (2015-Present)

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

Representative Publications

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1 April 2017 in Tourism Management
Verified
Journal Article
Open access
HZHong-yu Zhang
Hong-yu Zhang
PJPu Ji
Pu Ji
JWJian-Qiang Wang
Jian-Qiang Wang
XCXiao-Hong Chen
Xiao-Hong Chen

1 January 2015 in International Journal of Computational Intelligence Systems
Verified
Journal Article
Open access
PDF file
HZHong-yu Zhang
Hong-yu Zhang
PJPu Ji
Pu Ji
JWJian-qiang Wang
Jian-qiang Wang
XCXiao-Hong Chen
Xiao-Hong Chen
This paper presents a new correlation coefficient measure, which satisfies the requirement of this measure equaling one if and only if two interval neutrosophic sets (INSs) are the same. And an objective weight of INSs is presented to unearth and utilize deeper information that is uncertain. Using the proposed weighted correlation coefficient measure of INSs, a decision-making method is developed, which takes into account the influence of the evaluations' uncertainty and both the objective and subjective weights.

1 July 2018 in Information Sciences
Verified
Journal Article
Closed access
CZChenbin Zhang
Chenbin Zhang
HZHong-yu Zhang
Hong-yu Zhang
JWJian-qiang Wang
Jian-qiang Wang

30 October 2018 in IEEE Transactions on Systems, Man, and Cybernetics: Systems
Verified
Journal Article
Closed access
PJPu Ji
Pu Ji
HZHong-yu Zhang
Hong-yu Zhang
JWJian-qiang Wang
Jian-qiang Wang
Decision support is a vital function in electronic commerce (e-commerce). The purpose of this paper is to construct a review-based decision support model for items comparison in e-commerce. The proposed model uses probability multivalued neutrosophic linguistic numbers (PMVNLNs) to characterize online reviews. It overcomes the limitation of existing models by considering neutral information and hesitancy in text reviews. The fuzzy characterization of reviews (i.e., PMVNLN) can reflect similarities and differences in positive (negative) information. In addition, the model considers consumers' bounded rational behaviors by combining the regret theory with an outranking method. We empirically compare the proposed model with models in PConline.com and four existing models with data from PConline.com. The performance of these models in terms of accuracy is measured by the total relative difference metric. Results indicate the good performance of the proposed model. Our model is a promising option for e-commerce to provide consumers with good decision support service.

22 November 2016 in Neural Computing and Applications
Verified
Journal Article
Closed access
PDF file
PJPu Ji
Pu Ji
JWJian-Qiang Wang
Jian-Qiang Wang
HZHong-yu Zhang
Hong-yu Zhang

8 March 2017 in Neural Computing and Applications
Verified
Journal Article
Open access
PDF file
RLRu-Xia Liang
Ru-Xia Liang
JWJian-Qiang Wang
Jian-Qiang Wang
HZHong-yu Zhang
Hong-yu Zhang
Single-valued trapezoidal neutrosophic numbers (SVTNNs) have a strong capacity to depict uncertain, inconsistent, and incomplete information about decision-making problems. Preference relations represent a practical tool for presenting decision makers’ preference information regarding various alternatives. The purpose of this paper is to propose single-valued trapezoidal neutrosophic preference relations (SVTNPRs) as a strategy for tackling multi-criteria decision-making problems. First, this paper briefly reviews basic concepts about neutrosophic sets and SVTNNs and defines a new comparison method and new operations for SVTNNs. Next, two aggregation operators, the single-valued trapezoidal neutrosophic weighted arithmetic average operator and the single-valued trapezoidal neutrosophic weighted geometric average operator, are proposed for applications in information fusion. Then, this paper discusses the definitions of completely consistent SVTNPRs and acceptably consistent SVTNPRs. Finally, we outline a decision-making method based on SVTNPRs to address green supplier selection problems, and we conduct a comparison study and discussion to illustrate the rationality and effectiveness of the decision-making method.