Neuro-fuzzy and soft computing: a computational approach to learning and machine intelligence
Neuro-fuzzy and soft computing: a computational approach to learning and machine intelligence
Formalizing fuzzy spatial data model for integrating heterogeneous spatial data
Proceedings of the 2nd International Conference on Computing for Geospatial Research & Applications
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One of the major applications of geospatial information is to find the path or route between two locations. Though, several works have been carried out in finding the shortest or optimal path(s) between two locations; but not much efforts have been given in evaluating the suitability of a path with respect to various path attributes. In this paper, a fuzzy reasoning based approach has been proposed to find the suitability of a path/route based on its dimension, quality (i.e., texture and width) and the type of vehicle. The set of paths between two geographic locations are first determined using spatial topological reasoning. Then, the suitability of a path for a particular vehicle type is determined based on its length and quality, using fuzzy logic. The applicability of the proposed method has also been demonstrated.