Olutayo V.A

Work place: Computer Science Department, Joseph Ayo Babalola University, Ikeji-Arakeji, Nigeria

E-mail: vicsy2004@yahoo.com


Research Interests: Computer systems and computational processes, Computer Architecture and Organization, Data Mining, Data Structures and Algorithms, Mathematics of Computing


OLUTAYO V.A: Has M.Sc. in computer science from University of Ibadan, Nigeria. Post-graduate student for doctoral degree for computer science in University of Benin, Nigeria. Currently, an Assistant Lecturer in Computer Science Department Joseph Ayo Babalola University, Ikeji-Arakeji, Nigeria. Member, Computer Professionals Association of Nigeria (CPN). Major in Data Mining, and Service Oriented Computing.

Author Articles
Traffic Accident Analysis Using Decision Trees and Neural Networks

By Olutayo V.A Eludire A. A.

DOI: https://doi.org/10.5815/ijitcs.2014.02.03, Pub. Date: 8 Jan. 2014

This work employed Artificial Neural Networks and Decision Trees data analysis techniques to discover new knowledge from historical data about accidents in one of Nigeria’s busiest roads in order to reduce carnage on our highways. Data of accidents records on the first 40 kilometres from Ibadan to Lagos were collected from Nigeria Road Safety Corps. The data were organized into continuous and categorical data. The continuous data were analysed using Artificial Neural Networks technique and the categorical data were also analysed using Decision Trees technique .Sensitivity analysis was performed and irrelevant inputs were eliminated. The performance measures used to determine the performance of the techniques include Mean Absolute Error (MAE), Confusion Matrix, Accuracy Rate, True Positive, False Positive and Percentage correctly classified instances. Experimental results reveal that, between the machines learning paradigms considered, Decision Tree approach outperformed the Artificial Neural Network with a lower error rate and higher accuracy rate. Our research analysis also shows that, the three most important causes of accident are Tyre burst, loss of control and over speeding.

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