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  • 1
    Online-Ressource
    Online-Ressource
    Wiley ; 2018
    In:  Geographical Analysis Vol. 50, No. 4 ( 2018-10), p. 454-476
    In: Geographical Analysis, Wiley, Vol. 50, No. 4 ( 2018-10), p. 454-476
    Kurzfassung: In ubiquitous computing environments, with advanced Information and Communication Technologies, the availability of geographical data is rapidly improving. Spatial statistical services which is based on mathematics and geographic principles provide powerful tools to mine effective information from the rapid improving data. But how to help users to find the appropriate spatial statistical service is a serious challenge. Classification which can help to organize and manage the service effectively might be the key to solve it. However, traditional classifications which start from a certain perspective such as a service function or data source usually aim at a certain application. It is fixed and does not consider both the link between the different attributes and the demands of different users. Formal concept analysis (FCA) utilizes mathematical order theory and particularly the theory of complete lattices to comprehensively express the interrelationships between attributes and objects. Based on FCA, this article provides a dynamic classification pattern which take the relationships between these services and the characteristics of ubiquitous environments into consideration to help different users to complete the expected classification that meets their demands. Moreover, with this pattern, any number of additional categories could be added to the classification scheme flexibly. Two kinds of classification results that use three kinds of sensors and data types are presented to prove the feasibility and validity of the dynamic classification pattern.
    Materialart: Online-Ressource
    ISSN: 0016-7363 , 1538-4632
    URL: Issue
    RVK:
    Sprache: Englisch
    Verlag: Wiley
    Publikationsdatum: 2018
    ZDB Id: 2074885-1
    SSG: 14
    Standort Signatur Einschränkungen Verfügbarkeit
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  • 2
    Online-Ressource
    Online-Ressource
    The Pennsylvania State University Press ; 2021
    In:  Transportation Journal Vol. 60, No. 4 ( 2021-10-01), p. 339-366
    In: Transportation Journal, The Pennsylvania State University Press, Vol. 60, No. 4 ( 2021-10-01), p. 339-366
    Kurzfassung: In response to the increasingly frequent detour behavior of overloaded trucks attempting to avoid overload inspection and punishment, this article develops a bilevel programming model to optimize the routes of road administration vehicles by simulating the capture and anticapture interaction between administration vehicles and overloaded trucks. The upper-level model determines the optimal patrol routes of administration vehicles to maximize the number of overloaded trucks that can be captured. The lower-level model deduces the detour routes of overloaded trucks based on their circumvention behavior relative to administration vehicles. To solve the bilevel programming model, this article proposes a heuristic algorithm combining the ant colony algorithm and the labeling algorithm. To validate the proposed model and algorithm, this article uses actual rural highway data for Guiyang, China. The result proves the feasibility and superiority of the proposed programming model and algorithm. Compared to traditional overload management techniques, considering the detour behavior of overloaded trucks in optimizing the routing of road administration vehicles improves the effectiveness of overload management by up to 1.65 times.
    Materialart: Online-Ressource
    ISSN: 0041-1612 , 2157-328X
    Sprache: Englisch
    Verlag: The Pennsylvania State University Press
    Publikationsdatum: 2021
    ZDB Id: 2067107-6
    SSG: 3,2
    Standort Signatur Einschränkungen Verfügbarkeit
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