Investigating the relationship between adverse events and infrastructure development in an active war theater using soft computing techniques

    Authors

    E. Cakit; W. Karwowski; H. Bozkurt; T. Ahram; W. Thompson; P. Mikusinski;G. Lee

    Comments

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    Abbreviated Journal Title

    Appl. Soft. Comput.

    Keywords

    Infrastructure development; Adverse events; Soft computing; Artificial; neural networks (ANNs); Fuzzy inference system (FIS); Adaptive; neuro-fuzzy inference systems (ANFIS); Computer Science, Artificial Intelligence; Computer Science, ; Interdisciplinary Applications

    Abstract

    The purpose of this paper is to investigate the relationship between adverse events and infrastructure development investments in an active war theater by using soft computing techniques including fuzzy inference systems (FIS), artificial neural networks (ANNs), and adaptive neuro-fuzzy inference systems (ANFIS) where the accuracy of the predictions is directly beneficial from an economic and humanistic point of view. Fourteen developmental and economic improvement projects were selected as independent variables. A total of four outputs reflecting the adverse events in terms of the number of people killed, wounded or hijacked, and the total number of adverse events has been estimated. The results obtained from analysis and testing demonstrate that ANN, FIS, and ANFIS are useful modeling techniques for predicting the number of adverse events based on historical development or economic project data. When the model accuracy was calculated based on the mean absolute percentage error (MAPE) for each of the models, ANN had better predictive accuracy than FIS and ANFIS models, as demonstrated by experimental results. For the purpose of allocating resources and developing regions, the results can be summarized by examining the relationship between adverse events and infrastructure development in an active war theater, with emphasis on predicting the occurrence of events. We conclude that the importance of infrastructure development projects varied based on the specific regions and time period. (C) 2014 Elsevier B.V. All rights reserved.

    Journal Title

    Applied Soft Computing

    Volume

    25

    Publication Date

    1-1-2014

    Document Type

    Article

    Language

    English

    First Page

    204

    Last Page

    214

    WOS Identifier

    WOS:000344460600017

    ISSN

    1568-4946

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