[1] An integrated fuzzy regression – analysis of variance algo- rithm for improvement of electricity consumption estimation in uncertain environments. International Journal of Advanced Manufacturing Technology, 53: 645 – 660. https://doi.org/10.1007/s00170- 010-2862-5.
[2] Bolouri, S., Vafaeinejad, A., Alesheikh, A., Aghamohammadi, H. (2018). The ordered capacitated multi-Objective location-allocation problem for fire stations. Isprs International Journal of GeoIn- formation. 7(2): 44. https://doi.org/10.3390/ijgi7020044.
[3] Bolouri, S., Vafaeinejad, A., Alesheikh, A., Aghamohammadi, H. (2020). Location-Allocation prob- lem of fire stations in Tehran, region 22 using ”VAOMP” a unified approach. Geographical Planning of Space, 10(37): 43-56. doi: 10.30488/gps.2019.154046.2921.
[4] Challands, N. (2010). The relationships between fire service response time and fire outcomes. Fire Technology, 46(3), 665- 676.
[5] Chen, M., Wang, K., Dong, X., Li, H. ( 2020). Emergency rescue capability evaluation on urban fire stations in China, Process Safety and Environmental Protection, 135, 59-69, https://doi.org/10.1016/j.psep.2019.12.028.
[6] D’brot, C., Bravo, W., Arana, V. (2019). Optimum location and amount of new Fire Stations based on Geographic Information System and Analytic Hierarchy Methods. 2019 Congreso Internacional de Innovación y Tendencias en Ingenieria (CONIITI ), Bogota, Colombia. 1-6, doi: 10.1109/CONI- ITI48476.2019.8960912.
[7] Du, Y., Sun, J., Duan, Q., Qi, K., Xiao, H., Liew, K. M. (2020). Optimal assignments of allocating and scheduling emergency resources to accidents in chemical industrial parks, Journal of Loss Prevention in the Process Industries, 65:104-148, https://doi.org/10.1016/j.jlp.2020.104148.
[8] Erden, T., Coskun, M. (2010). Multi-criteria site selection for fire services: the interaction with analytic hierarchy process and geographic information systems. Natural Hazards and Earth System Sciences, 10(10): 2127-2134. https://doi.org/10.5194/nhess-10-2127-2010.
[9] Hajipour, V., Fattahi, P., Bagheri, H., Babaei Morad, S. (2022). Dynamic maximal covering loca- tion problem for fire stations under uncertainty: soft-computing approaches. International Journal of System Assurance Engineering and Management, 13(1): 90-112. https://doi.org/10.1007/s13198- 021-01109-8
[10] Handy, S., Paterson, R. G., Butler, K. (2003). Planning for street connectivity: getting from here to there (No. PAS Report No. 515).
[11] Haseltalab, M., Bioki, J., Bazafkan, E. and Naseri Tajvar, R., (2014), Determining the optimal lo- cation of the fire stations of the 6th district of Tehran municipality using MCDM-GIS integrated method. The 7th National Conference on Urban Planning and Management with Emphasis On urban development strategies, Mashhad, https://civilica.com/doc/435673.
[12] Huang, B., Liu, Chandramouli, M. (2006). A GIS supported Ant algorithm for the linear fea- ture covering problem with distance constraints. Decision Support Systems, 42(2): 1063-1075.
https://doi.org/10.1016/j.dss.2005.09.002.
[13] Indriasari, V., Mahmud, A., Ahmad, N., Shariff, A. (2010). Maximal service area problem for opti- mal siting of emergency facilities. International Journal of Geographical Information Science, 24(2): 213-230. https://doi.org/10.1080/13658810802549162.
[14] Kharaghani, H., Etemadfard, H., Salem Rafush, A. (2022). Allocation of fire stations by hybrid method (Case Study: Mashhad). Urban Management Studies, 13(48): 55-67. doi: 10.30495/ums.2022.19616.
[15] Kolesar, P., Walker, W. (1979). Measuring the travel characteristics of new york city’s fire compa- nies. New York, New York City RAND Institute, R-1449-NYC.
[16] Legates, D.R., McCabe, G.J. (1999). Evaluating the use of ”Goodness – of – fit” measures in hydrologic and hydroclimatic model validation. Water Resources Research, 35(1): 233-241. https://doi.org/10.1029/1998WR900018.
[17] Li, X., Zhao, Z., Zhu, X., Wyatt, T. (2011), Covering models and optimization techniques for emer- gency response facility location and planning: a review. Mathematical Methods of Operations Re- search, 74(3), 281-310.
[18] Mainak, B., Varun, S. )2016(. Development of agent-based model for predicting emergency response time. Perspectives in Science, 8, 138-141.
[19] Martín-Fernández, S., Martínez-Falero, E., Peribáñez, J.R., Ezquerra, A. (2021). GIS-Based simu- lated annealing algorithm for the optimum location of fire stations in the madrid region, spain: mon- itoring the collapse index. Applied Sciences, 11(18): 8414. https://doi.org/10.3390/app11188414.
[20] Murray, A., Tong, D. (2009). GIS and spatial analysis in the media. Applied Geography, :250-259.
[21] Nyimbili, P. H., Erden, T. (2020). GIS-based fuzzy multi-criteria approach for optimal site selection of fire stations in Istanbul, Turkey. Socio-Economic Planning Sciences, 71, 100860, https://doi.org/10.1016/j.seps.2020.100860.
[22] Park, P. Y., Jung, W. R., Yeboah, G., Rempel, G., Paulsen, D., Rumpel, D. (2016). First responders’ response area and response time analysis with/without grade crossing monitoring system. Fire Safety Journal, 79: 100-110.
[23] Poureskandar, A. (2002). Measuring the spatial distribution of fire accidents in the city using GIS. Master thesis, Tarbiat Modares University, Tehran.
[24] Pourramzan, E., Javan, F. (2016). Analysis of limits of safety and optimal positioning of fire stations by using GIS (case study : rasht). Territory, 13(50):1-16.
[25] Redden, D.T., Woodall, W.H. (1996). Further examination of fuzzy linear regression. Fuzzy Sets and Systems. 79(2): 203 – 211. https://doi.org/10.1016/0165-0114(95)00176-X.
[26] Shahparvari, S., Fadaki, M., Chhetri, P. (2020). Spatial accessibility of fire sta- tions for enhancing operational response in Melbourne. Fire Safety Journal, 117. https://doi.org/10.1016/j.firesaf.2020.103149.
[27] Shiri, F., Shams, M. (2016). factors affecting location of fire stations using cluster anal- ysis technique. environmental based territorial planning (amayesh), 9(33), 113-132. sid. https://sid.ir/paper/130776/en.
[28] Shurvarzi, H., mesgari, M., Alimohammadi, A., Aghamohamadian, H. (2012). Assessing the ca- pability of meta-heuristic algorithms in location-finding for firefighting centers. Spatial Planning (Modares Human Sciences), 16(3):, 1-29. sid. https://sid.ir/paper/171917/en.
[29] Tamat, A., Pawanchik, S., Kamil, A. A., Hilmi, M. F., Lateh, H. H., Hasan, M. Z., Ferdushi, K. F., Hossain, M. K. (2014). An analysis of variation of turn out time and response time in Penang state fire and rescue department, Journal of Environmental Science and Technology, 7, 200- 208.
[30] Tanaka, H., Uejima, S., Asai, K. (1982). Fuzzy linear model, fuzzy linear regres- sion model. IEEE Transactions on Systems Man and Cybernetics. 12: 903 – 907. http://dx.doi.org/10.1109/TSMC.1982.4308925.
[31] Tashakor, Z. (1999). Fire departments and structural deficiencies. Municipalities, 10.
[32] Uddin, Md. Sh., Warnitchai, P. (2020). Decision support for infrastructure planning: a comprehen- sive location–allocation model for fire station in complex urban system. Natural Hazards, 102(3): 1475-1496. 10.1007/s11069-020-03981-2.
[33] Yang, L., Jones, B. F., Yang, S.H. (2007). A fuzzy multi-objective programming for optimization of fire station locations through genetic algorithms. European Journal of Operational Research, 181, 903-915.
[34] Zhang, W., Jiang, J. C. (2011). Research on the location of fire station based on GIS and GA. Applied Mechanics and Materials, 130–134, 377–380. https://doi.org/10.4028/www.scientific.net/amm.130-
134.377.