%0 Journal Article %A WANG Xiaonan1 %A 2 %A JU Yongfeng1 %A GAO Ting1 %T Method of traffic flow model selection based on hesitant fuzzy Heronian mean %D 2017 %R 10.3778/j.issn.1002-8331.1610-0020 %J Computer Engineering and Applications %P 134-140 %V 53 %N 13 %X To deal with Multi-Attribute Decision Making(MADM) problems when the attribute values are in the form of hesitant fuzzy information and the input arguments are associated with each other, a novel Hesitant Fuzzy Heronian Mean(HFHM) operator is proposed on the basis of Archimedean norm and Heronian mean. Then, the properties of the HFHM operator are studied in detail. Furthermore, some special cases of the HFHM operator are discussed and the Hesitant Fuzzy Weighted Heronian Mean(HFWHM) operator is presented. In addition, a new hesitant fuzzy MADM method based on HFWHM operator is developed, which can capture the interrelationships among the input arguments and enable decision maker to make decision with different parameters in accordance with their own risk preference attitude. In the end, a numerical example about traffic flow model selection is provided to illustrate the effectiveness of the proposed method. %U http://cea.ceaj.org/EN/10.3778/j.issn.1002-8331.1610-0020