SVM Based Spatial Data Mining for Traffic Risk Analysis
Roopesh Kumar, Diljeet Singh Chundawat, Prabhat Kumar Singh · 2014
Abstract:- Extracting knowledge from spatial data like GIS data is important to reduce the data and extract information. GIS data also contains information about accidents at certain place and road conditions. Such data contains useful information for the traffic risk analysis. But such information are not directly present in the dataset. Hence spatial data mining technique is needed to extract knowledge from these databases. The previous work shows unpractical approach to multi- layer geo-data mining. That means the information from various sources are combined based on the data relation and data mining is performed on the relation. The efficiency of risk factor evaluation requires Key Word:- GIS, SVM,Clustering,Geo-Datamining, Ant Colony Optimization