• Jun 14, 2017 News!Vol.6, No.3 has been indexed by EI(Inspec)!   [Click]
  • May 03, 2016 News!Vol.5, No.5 has been indexed by EI(Inspec)!   [Click]
  • May 03, 2016 News!Vol.5, No.4 has been indexed by EI(Inspec)!   [Click]
General Information
    • ISSN: 2010-3700
    • Frequency: Bimonthly
    • DOI: 10.18178/IJMLC
    • Editor-in-Chief: Dr. Lin Huang
    • Executive Editor:  Ms. Cherry L. Chen
    • Abstracing/Indexing: Engineering & Technology Digital Library, Google Scholar, Crossref, ProQuest, Electronic Journals Library, DOAJ and EI (INSPEC, IET).
    • E-mail: ijmlc@ejournal.net
Editor-in-chief
Dr. Lin Huang
Metropolitan State University of Denver, USA
It's my honor to take on the position of editor in chief of IJMLC. We encourage authors to submit papers concerning any branch of machine learning and computing.
IJMLC 2015 Vol. 5(3): 252-257 ISSN: 2010-3700
DOI: 10.7763/IJMLC.2015.V5.516

Assessing the Relationship between Economic Factors and Adverse Events in an Active War Theater Using Fuzzy Inference System Approach

Erman Cakit and Waldemar Karwowski
Abstract—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.

Index Terms—Adverse events, fuzzy inference system, human social cultural behavior (HSCB) modeling, infrastructure development.

E. Cakit is with the Department of Industrial Engineering, Aksaray University, 68100, Aksaray, Turkey (e-mail: ermancakit@aksaray.edu.tr).
W. Karwowski is with the Department of Industrial Engineering and Management Systems, University of Central Florida, Florida, FL 32816-2450 USA (e-mail: wkar@ucf.edu).

[PDF]

Cite: Erman Cakit and Waldemar Karwowski, "Assessing the Relationship between Economic Factors and Adverse Events in an Active War Theater Using Fuzzy Inference System Approach," International Journal of Machine Learning and Computing vol. 5, no. 3, pp. 252-257, 2015.

Copyright © 2008-2015. International Journal of Machine Learning and Computing. All rights reserved.
E-mail: ijmlc@ejournal.net