Introduction to artificial neural systems
Introduction to artificial neural systems
C4.5: programs for machine learning
C4.5: programs for machine learning
Machine Learning
A Novel Neural Network Technique for Modeling Data Containing Multiple Functions
Proceedings of the International Conference on Computational Intelligence, Theory and Applications
Artificial Intelligence and Law
Urban 3D GIS Modeling of Terrorism Sniper Hazards
Social Science Computer Review
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Crime rates differ between types of urban district, and these disparities are best explained by the variation in use of urban sites by differing populations. A database of violent incidents is rich in spatial information and studies have, to date, provided a statistical analysis of the variables within this data. However, a much richer survey can be undertaken by linking this database with other spatial databases, such as the Census of Population, weather and police databases. Coupling Geographical Information Systems (GIS) with Artificial Neural Networks (ANN) offers a means of uncovering hidden relationships and trends within these disparate databases. Therefore, this paper outlines the first stage in the development of such a system, designed to facilitate the prediction of crime hot spots. For this stage, a series of Kohonen Self-Organising Maps (KSOM) will be used to cluster the data in a way that should allow common features to be extracted.