Assessing the Relationship between Economic Factors and Adverse Events in an Active War Theater Using Fuzzy Inference System Approach
Erman Çakıt, Waldemar Karwowski · International Journal of Machine Learning and Computing · 2015
The main purpose of this study was to investigate the relationship between adverse events and infrastructure development investments by estimating the number of adverse events in an active war theater based on the allocation of infrastructure development projects utilizing a fuzzy inference systems (FIS) approach.The considered model input variables included the total number of economic improvement projects and their associated budgets at different time periods in Afghanistan between 2002 and 2009.The output variables were the estimated numbers of people killed, wounded, and hijacked in different sectors of Afghanistan in 2010.Six different prediction models were developed and tested with an independent datasets.The prediction accuracy of each FIS model was evaluated and compared based on the mean absolute errors (MAE).It was concluded that the FIS is a useful modeling approach that can be applied under scenario-based conditions to support decision makers in analyzing historical economic data on how allocation of regional infrastructure development funds can best help reducing the onset of adverse events in an active war theater.