Cluster (spacecraft)

Accident (philosophy)

Mathematics

Intersection (aeronautics)

Operating system

Data mining

Statistics

Data collection

Epistemology

Engineering

Philosophy

Artificial intelligence

Systems engineering

Geography

Association rule learning

Programming language

Transport engineering

Scale (ratio)

Road accident

Computer science

Task (project management)

Cartography

Cluster analysis

Process (computing)

Journal of Computational and Theoretical Nanoscience

This report shows the outcome by applying large scale data mining techniques on the Finnish roads. From the research study it is very difficult task to perform because the collected data have uncertainty, incomplete and error values. So the data exploration is a challenging task. The data used in the process have been collected from Finnish road administration data sets. The data used in the process have been collected from Finnish road administration data sets. The main target of our project is to look into practicability of Robust clustering, to find the associations and repeated item sets and applying apprehend methods for the analysis of road accidents. While the results display the selected mining techniques and methods were capable to the understandable patterns. To calculate the accident frequency count as a parameter /c-means algorithm is used to cluster the locations. To characterize the surface conditions association rule mining is used. data mining skills disclosed different environmental reasons associated with road accidents. Intersection on highways have been identified as a dangerous for fatal accidents.

Car Accident Detection and Notification System Using Smartphone