Anomalies Calculation and Detection in Fuel Expense through Data Mining

In organizations having large vehicle fleet a reasonable portion of the fuel budget is misused by malpractices of drivers and fuel providers. An optimal usage of this fuel amount could be of big advantages to the organization. We proposed a novel anomaly %age calculation algorithm to determine the misuse of the fuel of the vehicles. This algorithm will reduce the efforts for anomaly detection in clustering process. The results reflect that this algorithm could be used to implement an effective check on the misuse of the fuel in big organizations with less effort.