Abstract
Complex systems such as transportation are influenced by several factors which are subjugated by uncertainty and therefore, it has non-linear characteristics. Consequently, transition in congestion degree from one class to another class can be abrupt and unpredictable. If the possibility of transition in congestion degree from one class to another can be determined, then adequate measures can be taken to make transportation system more robust and sustainable. The present paper demonstrates the efficacy of Bayesian-Fuzzy GIS Overlay to construe congestion dynamics on a test data set. The test data set consists of congestion indicators such as Average Speed (AS) and Congestion Index Value (CIV) of different routes for the test study area. The results succeeded in representing the probable transition in congestion degree from one class to another with respective Bayesian probabilities for different classes.
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Acknowledgements
The authors are grateful to the Vice Chancellor, Birla Institute of Technology, Mesra, and Ranchi for providing research facilities to perform the investigation in Geographic Information System (GIS) & Digital Image Processing (DIP) labs of the Department of Remote Sensing, BIT Mesra, Ranchi.
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Mukherjee, A.B., Krishna, A.P., Patel, N. (2016). Bayesian-Fuzzy GIS Overlay to Construe Congestion Dynamics. In: Satapathy, S., Mandal, J., Udgata, S., Bhateja, V. (eds) Information Systems Design and Intelligent Applications. Advances in Intelligent Systems and Computing, vol 433. Springer, New Delhi. https://doi.org/10.1007/978-81-322-2755-7_42
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DOI: https://doi.org/10.1007/978-81-322-2755-7_42
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