Abstract
In this paper a hybrid fuzzy inference and transfer function modeling is used to predict the irregular human behavior during hard and stressful tasks such as dangerous military missions. a set of affecting factors such as missioner's experience, fatigue, sunshine intensity, hungriness, thirstiness, psychological characteristics, affright, etc. may be taken to account. in this regard a dynamic system model is used to predict the convolution of the timed effects of different factors on irregular behavior of personnel during the mission. This approach of predicting irregular behavior or erroneous decision making of staff have serious usages in aerospace, military, social and similar projects where a wrong decision can have catastrophic outcome such as attempting to suicide by a pilot or killing civilians by a soldier in stressful situations. the effect of such behavior and decisions may even cause the failure of the overall project or mission. for example, killing civilians by a soldier can result to the overall failure of human terrain missions where the main objective is gaining trust between the local civilian population. © 2012 Published by Elsevier B.V.
Recommended Citation
S. Khanmohammadi et al., "A Fuzzy Inference Model for Predicting Irregular Human Behaviour during Stressful Missions," Procedia Computer Science, vol. 12, pp. 265 - 270, Elsevier, Jan 2012.
The definitive version is available at https://doi.org/10.1016/j.procs.2012.09.067
Department(s)
Engineering Management and Systems Engineering
Publication Status
Open Access
Keywords and Phrases
Convolution; Decision Making; Dynamic System; Fuzzy Inference; Human Resources; Irregular Human Behaviour; Risk; Stress
International Standard Serial Number (ISSN)
1877-0509
Document Type
Article - Conference proceedings
Document Version
Final Version
File Type
text
Language(s)
English
Rights
© 2024 Elsevier, All rights reserved.
Creative Commons Licensing
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.
Publication Date
01 Jan 2012