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        Hybrid monotonic inclusion measures for interval-valued hesitant fuzzy sets

        Xiaoxia Ren,Hong Wang 원광대학교 기초자연과학연구소 2017 ANNALS OF FUZZY MATHEMATICS AND INFORMATICS Vol.13 No.5

        The inclusion measure indicates the degree to which a given partially ordered set is contained in another one. Hybrid monotonic inclusion measure is the rational generalization of inclusion measure. So, the main purpose of this paper is to introduce the hybrid monotonic inclusion measure for interval-valued hesitant fuzzy sets (IVHFSs). Firstly, we present the construction approaches to hybrid monotonic inclusion measures between any two interval-valued hesitant fuzzy elements (IVHFEs) under different order relationships in extended environment. In addition, a new partial order relationship $\leq_{\vee}$ for IVHFEs is also defined, and then some hybrid monotonic inclusion measures under the new partial order $\leq_{\vee}$ for IVHFEs and IVHFSs will be constructed and be proved in detail. Finally, we present some new formulas to calculate the similarity measure and fuzzy entropy derived from the hybrid monotonic inclusion measure for IVHFSs.

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        Spatiotemporal Variations and Possible Sources of Ambient PM10 from 2003 to 2012 in Luzhou, China

        Dong Ren,Youping Li,Hong Zhou,Xiaoxia Yang,Xiaoman Li,Xuejun Pan,Bin Huang 대한환경공학회 2014 Environmental Engineering Research Vol.19 No.4

        Descriptive statistics methods were used to study the spatiotemporal variations and sources of ambient particulate matter (PM10) in Luzhou, China. The analyzed datasets were collected from four national air quality monitoring stations: Jiushi (S1), Xiaoshi (S2), Zhongshan (S3), Lantian (S4) over the period of 2003-2012. This city was subjected serious PM10 pollution, and the long-term annual average PM10 concentrations varied from 76 to 136 μg/m3. The maximum concentration was more than 3-fold of the annual average (40 μg/m3) issued by EPA-China for the ambient air quality. General temporal pattern was characterized by high concentrations in winter and low concentrations in summer, and general spatial gradient was in the reduction order of S2 > S4 > S3 > S1, which were both due to different particulate contributors and special meteorological conditions. The source apportionment indicated that vehicular emissions, road dusts, coal burning and chemical dusts were the major contributors of the identified PM10 pollution, and the vehicular emissions and the road wear re-suspended particles dominated the heavy PM10 pollution in recent years. Two other potential sources, agricultural and celebration activities could decrease the air quality in a short term. Finally, some corresponding suggestions and measures were provided to improve the air quality.

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