Benesty, J., Chen, J., Huang, Y. and Cohen, I. (2009). Pearson correlation coefficient, in J. Cohen et al. (Eds), Noise Reduction in Speech Processing, Springer, Berlin/Heidelberg, pp. 1–4.10.1007/978-3-642-00296-0_5
Chabir, K., Rhouma, T., Keller, J.Y. and Sauter, D. (2018). State filtering for networked control systems subject to switching disturbances, International Journal of Applied Mathematics and Computer Science 28(3): 473–482, DOI: 10.2478/amcs-2018-0036.10.2478/amcs-2018-0036
Chai, T. and Draxler, R.R. (2014). Root mean square error (RMSE) or mean absolute error (MAE), Geoscientific Model Development Discussions 7(1): 1525–1534.10.5194/gmdd-7-1525-2014
Chmielewski, M., Kukie, M., Fr, D., Kukiełka, M., Frąszczak, D. and Bugajewski, D. (2018). Military and crisis management decision support tools for situation awareness development using sensor data fusion, in J.Świ ˛atek et al. (Eds), Information Systems Architecture and Technology: Proceedings of the 38th International Conference on Information Systems Architecture and Technology, ISAT 2017, Springer, Cham, pp. 189–199.10.1007/978-3-319-67229-8_17
El-Douh, A.A.-R., Lu, S.F., Elkouny, A.A. and Amein, A. (2022). Hybrid cryptography with a one-time stamp to secure contact tracing for COVID-19 infection, International Journal of Applied Mathematics and Computer Science 32(1): 139–146, DOI: 10.34768/amcs-2022-0011.
Hu, X., Lai, F., Chen, G., Zou, R. and Feng, Q. (2019). Quantitative research on global terrorist attacks and terrorist attack classification, Sustainability 11(5): 1487.10.3390/su11051487
Janis, I.L. and Mann, L. (1977). Emergency decision making: A theoretical analysis of responses to disaster warnings, Journal of Human Stress 3(2): 35–48.10.1080/0097840X.1977.9936085864252
Junosza-Szaniawski, K., Nogalski, D. and Rzążewski, P. (2022). Exact and approximation algorithms for sensor placement against DDoS attacks, International Journal of Applied Mathematics and Computer Science 32(1): 35–49, DOI: 10.34768/amcs-2022-0004.
Kebir, O., Nouaouri, I., Belhadj, M. and Ben Said, L. (2020a). A multi-agent model for countering terrorism, in H. Fujita et al. (Eds), Knowledge Innovation Through Intelligent Software Methodologies, Tools and Techniques: Proceedings of the 19th International Conference on New Trends in Intelligent Software Methodologies, Tools and Techniques (SoMeT_20), IOS Press, Amsterdam, p. 260.10.3233/FAIA200571
Kebir, O., Nouaouri, I., Belhadj, M. and Bensaid, L. (2020b). A multi-agent model for countering terrorism, Proceedings of the 33rd International Conference on Industrial, Engineering & Other Applications of Applied Intelligent Systems (IEA/AIE_20), Kitakyushu, Japan, pp. 1–8.10.3233/FAIA200571
Kebir, O., Nouaouri, I., Belhaj, M., Ben Said, L. and Akrout, K. (2020c). A multi-agent architecture for modeling organizational planning against terrorist attacks in urban areas, 2020 International Multi-Conference on Organization of Knowledge and Advanced Technologies (OCTA), Tunis, Tunisia, pp. 1–8.10.1109/OCTA49274.2020.9151843
Kebir, O., Nouaouri, I., Belhaj, M., Said, L.B. and Akrout, K. (2020d). MAMCTA—Multi-agent model for counter terrorism actions, Revue de l’Information Scientifique et Technique 25(1): 76–90.
Kebir, O., Nouaouri, I., Rejeb, L. and Said, L.B. (2022). Simulating actors’ behaviors within terrorist attacks scenarios based on a multi-agent system, Proceedings of the 12th International Defence and Homeland Security Simulation Worskhop (DHSS 2022), Rome, Italy, pp. 12–20.
Kebir, O., Nouaouri, I., Rejeb, L. and Said, L.B. (2021). Conceptual terrorist attacks classification: Pre-processing for artificial intelligence-based classification, Proceedings of the 11th International Defence and Homeland Security Simulation Workshop (DHSS 2021), Kraków, Poland, pp. 16–24.
Kress, M., Caulkins, J.P., Feichtinger, G., Grass, D. and Seidl, A. (2018). Lanchester model for three-way combat, European Journal of Operational Research 264(1): 46–54, DOI: 10.1016/j.ejor.2017.07.026.10.1016/j.ejor.2017.07.026
Kress, M. and Szechtman, R. (2009). Why defeating insurgencies is hard: The effect of intelligence in counter-insurgency operations—A best-case scenario, Operations Research 57(3): 578–585.10.1287/opre.1090.0700
Lee, H.-K. and Zo, H. (2017). Assimilation of military group decision support systems in Korea: The mediating role of structural appropriation, Information Development 33(1): 14–28.10.1177/0266666916628316
Lucas, T.W. and McGunnigle, J.E. (2003). When is model complexity too much? Illustrating the benefits of simple models with Hughes’ salvo equations, Naval Research Logistics 50(3): 197–217.10.1002/nav.10062
Oladejo, M., Udoh, I. and Abam, A. (2020). Optimizing the community’s supports in counter-terrorism operations: A sticks–carrots game theoretic model, Journal of Applied Science and Technology 39(47): 45–67.10.9734/cjast/2020/v39i4731186
Osoba, O.A. and Kosko, B. (2017). Fuzzy cognitive maps of public support for insurgency and terrorism, Journal of Defense Modeling and Simulation 14(1): 17–32.10.1177/1548512916680779
Pagán, J.V. (2010). Improving the classification of terrorist attacks: A study on data pre-processing for mining the Global Terrorism Database, ICSTE 2010—2nd International Conference on Software Technology and Engineering, Puerto Rico, USA, Vol. 1, pp. 104–110.
Pechenkina, A.O. and Bennett, D.S. (2017). Violent and non-violent strategies of counterinsurgency, Journal of Artificial Societies and Social Simulation 20(4): 11.10.18564/jasss.3540
Saltelli, A. and Annoni, P. (2010). How to avoid a perfunctory sensitivity analysis, Environmental Modelling & Software 25(12): 1508–1517.10.1016/j.envsoft.2010.04.012
Seehuus, R.A., Rise, Ø.R., Hannay, J.E., Wold, R. and Matlary, P. (2020). Cloud-based decision support system for planning military operations, Technical report, Norwegian Military Academy, Oslo.
Sumithra, S. and Vadivel, R. (2021). An optimal innovation based adaptive estimation Kalman filter for accurate positioning in a vehicular ad-hoc network, International Journal of Applied Mathematics and Computer Science 31(1): 45–57, DOI: 10.34768/amcs-2021-0004.
Udoh, I. and Oladejo, M. (2019). Optimal human resources allocation in counter-terrorism (CT) operation: A mathematical deterministic model, International Journal of Advances in Scientific Research and Engineering 5(1): 96–115.10.31695/IJASRE.2019.33008
Şuşnea, E. (2012). Decision support systems in military actions: Necessity, possibilities and constraints, Journal of Defense Resources Management 3(2): 131–140.
Vilanova, A., Telea, A., Scheuermann, G. and Möller, T. (2008). Investigative visual analysis of global terrorism, Eurographics, Crete, Greece, Vol. 27, p. 2008.