Fuzzy ınference modeling with the help of fuzzy clustering for predicting the occurrence of adverse events in an active theater of war
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Dosyalar
Tarih
2015
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Taylor and Francis Inc.
Erişim Hakkı
info:eu-repo/semantics/embargoedAccess
Özet
This study investigated the relationship between adverse events and infrastructure development projects in an active theater of war using fuzzy inference systems (FIS) with the help of fuzzy clustering that directly benefits from its prediction accuracy. Fourteen developmental and economic improvement projects were selected as independent variables. These were based on allocated budgets and included a number of projects from different time periods, urban and rural population density, and total number of adverse events during the previous month. 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 performance of each model was investigated and compared to all other models with calculated mean absolute error (MAE) values. Prediction accuracy was also tested within ±1 (difference between actual and predicted value) with values around 90%. Based on the results, it was concluded that FIS is a useful modeling technique for predicting the number of adverse events based on historical development or economic project data. © 2015 Taylor & Francis Group, LLC.
Açıklama
Çakıt, Erman (Aksaray, Yazar)
Anahtar Kelimeler
Kaynak
Applied Artificial Intelligence
WoS Q Değeri
N/A
Scopus Q Değeri
Q2
Cilt
29
Sayı
10
