Optimal Decision Maker Algorithm for I2Sim Using ANN, Neuro Fuzzy and Fuzzy
DOI:
https://doi.org/10.18486/ijcsnt/10.2.135Keywords:
I2SIM, Neuro Fuzzy, Decision Maker, OptimizationAbstract
The aim of this paper is to design an optimal decision maker algorithm for I2SIM using Fuzzy, Neuro fuzzy and Artificial Neural Network (ANN). The objective is to minimize the deaths in the system through controlling the distributor outputs. Three controllers are designed that is able to optimize resource usage following an infrastructure disruption. These controllers are designed in MATLAB and then implemented in I2SIM. From the results, the controller which gives the best distribution output will be determined. The goal of the controller is to maximize an output, which in this case is the number of discharged/healed patients from the hospitals. The results of the controller will be compared and analyzed to determine which technique gives the best result.
References
Khouj, M. T., Sarkaria, S., and Marti, J. R. (2014). Decision assistance agent in real-time simulation. International Journal of Critical Infrastructures. The University of British Columbia, Vancouver. DOI: https://doi.org/10.1504/IJCIS.2014.062968
Khouj, M. (2014). Resource Allocation Optimization of a Disrupted Interdependent System Using Machine Learning.
Bai, M. (2012). Optimization Decision Maker Algorithm for Infrastructure Interdependencies with I2Sim Applications. The University of British Columbia, Vancouver, July 2012.
Wang, K., Bai, M., Marti, J., and Srivastava, K. D. (2012). Optimal Decision Maker Algorithm for Disaster Response Management with I2Sim Applications. Proceedings of the 9th International ISCRAM Conference, Vancouver, Canada, April 2012.
Khouj, M., Lopez, C., Sarkaria, S., and Marti, J. (2011). Disaster Management in Real Time Simulation Using Machine Learning. Canadian Conference on Electrical and Computer Engineering, 1507–1510. DOI: https://doi.org/10.1109/CCECE.2011.6030716
I2Sim. (2007). Infrastructure Interdependencies Simulation (I2Sim) Team. Available from: www.i2sim.ca. Date accessed: March 05, 2013.
Marti, J. R., Hollman, J. A., Ventura, C., and Jatskevich, J. (2006). Design for Survival Real-Time Infrastructures Coordination. University of British Columbia, Department of Electrical and Computer Engineering.
Jain, S., and McLean, C. (2003). A Framework for Modeling and Simulation for Emergency Response. Available from: http://www.informs-sim.org/wsc03papers/132.pdf. Date accessed: March 14, 2013. DOI: https://doi.org/10.6028/NIST.IR.7071
Rahman, H. A., Armstrong, M., Mao, D., and Marti, J. R. (2008). I2Sim: A Matrix-partition based Framework for Critical Infrastructure Interdependencies Simulation. 2008 IEEE Electrical Power & Energy Conference. DOI: https://doi.org/10.1109/EPC.2008.4763353
Ventura, C. E., Juarez Garcia, H., Thibert, K. M., Martí, J., and Hollman, J. (2008). Mapping of Interdependencies through Integrated Hazard Analysis: Study case of a Canadian University Campus. The 14th World Conference on Earthquake Engineering, October 12–17, 2008, Beijing, China.
Stergiou, C., and Siganos, D. (2010). Neural Networks. Available from: http://www.doc.ic.ac.uk/~nd/surprise_96/journal/vol4/cs11/report.html. Date accessed: November 2014.
Paplinski, A. (2005). Neuro-Fuzzy Computing. Available from: www.csse.monash.edu.au/courseware/cse5301/2006/Lnts/L12fz.pdf. Date accessed: November 2014.
Sheu, J.-B. (2007). An emergency logistics distribution approach for quick response to urgent relief demand in disasters. Transportation Research Part E: Logistics and Transportation Review, 43(6), 687–709. DOI: https://doi.org/10.1016/j.tre.2006.04.004
Wang, W., Liu, M., and Wang, L. (2010). The dynamic optimal method of emergency resources deployment planning based on Markov decision processes. Acta Scientiarum Naturalium Universitatis Nankaiensis (Natural Science Edition), 43(3), 18–23.
Wang, Y., and Perkins, J. R. (2002). Optimal Resource Allocation in New Product Development Projects: A Control-Theoretic Approach. IEEE Transactions on Automatic Control, 47, 1267–1276. DOI: https://doi.org/10.1109/TAC.2002.800740
Vieira, J., Dias, F. M., and Mota, A. (2001). Neuro-Fuzzy System—A Survey. Available from: www.cee.uma.pt/morgado/down/483-343.pdf. Date accessed: January 2016.
Arboleda, C. A., Abraham, D. M., Richard, J.-P. P., and Lubitz, R. (2009). Vulnerability assessment of health care facilities during disaster events. Journal of Infrastructure Systems, 15(3), 149–161. DOI: https://doi.org/10.1061/(ASCE)1076-0342(2009)15:3(149)
Wu, S., Shuman, L., Bidanda, B., Kelley, M., Sochats, K., and Balaban, C. (2008). Agent-based discrete event simulation modeling for disaster responses. Proceedings of the 2008 Industrial Engineering Conference.
Eusgeld, I., Nan, C., and Dietz, S. (2011). System-of-system approach for interdependent critical infrastructures. Reliability Engineering & System Safety, 96(6), 679–686. DOI: https://doi.org/10.1016/j.ress.2010.12.010
Atanasiu, G. M., and Leon, F. (2013). Agent-based risk assessment and mitigation for urban public infrastructure. Forensic Engineering 2012, 418–427. DOI: https://doi.org/10.1061/9780784412640.045
Fiedrich, F., Gehbauer, F., and Rickers, U. (2000). Optimized resource allocation for emergency response after earthquake disasters. Safety Science, 35(1), 41–57. DOI: https://doi.org/10.1016/S0925-7535(00)00021-7
Das, H., Naik, B., and Behera, H. S. (2018). Classification of diabetes mellitus disease (DMD): A data mining (DM) approach. In Progress in Computing, Analytics and Networking, 539–549. Springer, Singapore. DOI: https://doi.org/10.1007/978-981-10-7871-2_52
Meher, S. K. (2017). Efficient pattern classification model with neuro-fuzzy networks. Soft Computing, 21(12), 3317–3334. DOI: https://doi.org/10.1007/s00500-015-2010-0
Skrjanc, I., Iglesias, J. A., Sanchis, A., Leite, D., Lughofer, E., and Gomide, F. (2019). Evolving fuzzy and neuro-fuzzy approaches in clustering, regression, identification, and classification: A survey. Information Sciences, 490, 344–368. DOI: https://doi.org/10.1016/j.ins.2019.03.060
Downloads
Published
Issue
Section
License
Copyright (c) 2021 Kevin Ramkay-Henry
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
