ارائه مدل مدیریت واحد بحران‌های شهر هوشمند از منظر پدافند غیرعامل مبتنی بر شیوه‌های AHP و ANFIS

نوع مقاله : مقاله پژوهشی

نویسندگان

گروه مهندسی عمران، واحد تهران جنوب، دانشگاه آزاد اسلامی، تهران، ایران.

چکیده

امروزه رشد جمعیت و به‌تبع آن افزایش تمایل به شهرنشینی، به‌خصوص در کشورهای درحال‌توسعه، موجب بروز مشکلات محیط‌زیستی، اقتصادی، اجتماعی و امنیتی شده است که ادامه وضع موجود، امکان توسعه پایدار شهری را ناممکن می‌سازد. از طرفی، طی سالیان اخیر، توجه به مباحث پدافند غیرعامل در بسیاری از کشورها موردتوجه قرار گرفته است. اینجاست که شهر هوشمند به‌عنوان راه‌حل ایده‌آل مقابله با چالش‌های ناشی از شهرنشینی مطرح می‌گردد. در این پژوهش، ابتدا معیارهای مهم مدیریت واحد بحران‌های شهر هوشمند با تاکید بر پدافند غیرعامل شناسایی گردید و میزان اهمیت هریک از آن‌ها مشخص شد و سپس نتایج آن‌ها مورد بررسی قرار گرفت. روش گردآوری اطلاعات در پژوهش حاضر، از نوع توصیفی- تحلیلی بر پایه مطالعات کتابخانه‌ای است. اطلاعات لازم در این پژوهش، با استفاده از مطالعات کتابخانه‌ای و همچنین، ضمن تکمیل چک‌لیست به‌صورت کیفی جمع‌آوری‌شده و پس از آن برای انجام محاسبات ازنظر کارشناسان خبره در زمینه پدافند غیرعامل و شهر هوشمند استفاده ‌شد. سپس با استفاده از فرآیند تحلیل سلسله‌مراتبی AHP، شاخص‌های تعیین شده، امتیازدهی و رتبه‌بندی گردیدند و در ادامه با استفاده از نرم‌افزار MATLAB R2021b، اقدام به کدنویسی روش سیستم استنتاج فازی- عصبی تطبیقی (ANFIS)، شد که درنهایت منجر به طراحی و ارائه مدل مدیریت واحد بحران‌های شهر هوشمند از منظر پدافند غیرعامل گردید. یافته‌های حاصل از پژوهش حاضر مبتنی بر شیوه‌های AHP و ANFIS، نشان از اهمیت ایمن‌سازی اینترنت اشیا (IoT)، ایمن‌سازی محیط، ایمن‌سازی شبکه، کنترل‌پذیرش شبکه، ایجاد نرم‌افزار مجازی‌سازی در سطح سیستم‌عامل (کانتینر)، کاهش تهدید و اصلاح، و تجزیه‌وتحلیل و اقدام در بحث مدیریت واحد بحران‌های شهر هوشمند از منظر پدافند غیرعامل دارد. باتوجه‌به اهمیت موضوع ایجاد شهرهای هوشمند، می‌توان گفت که لزوم بررسی و توجه همه‌جانبه به مدیریت واحد بحران‌های شهرهای هوشمند باتوجه‌به اصول و مبانی پدافند غیرعامل، تأثیر بیشتری را در برقراری حفاظت، امنیت و افزایش توسعه پایدار شهری دارد؛ بنابراین کلیه شاخص‌های مهم دراین‌خصوص به‌تفکیک مورد ارزیابی قرار گرفت و مدل نهایی ارائه گردید. مدل ارائه شده دارای نسبت سازگاری نهایی 0/059 بوده که قابل‌قبول است. همچنین مقدار خطای RMSE شبکه آموزش‌دیده ANFIS، برابر0/0179 و مقدار R2 آن نیز برابر 0/9897 بدست آمد که نشان از دقت بسیار بالای مدل پیشنهادی دارد.

کلیدواژه‌ها

موضوعات

عنوان مقاله [English]

Presenting a Model for Integrated Crisis Management in Smart Cities from the Viewpoint of Passive Defense Based on AHP and ANFIS

نویسندگان [English]

  • Seyed Azim Hosseini
  • Hossein Maleki Toulabi
Associate Professor, Department of Civil Engineering, South Tehran Branch, Islamic Azad University, Tehran, Iran.
چکیده [English]

Currently, the ever-increasing population growth coupled with the people’s tendency toward urbanization, especially in developing countries, has led to a number of environmental, economic, social, and security problems, to a point where continuation of the current trends is likely to prevent sustainable urban development. On the other hand, passive defense has gained lots of attention in many countries in the recent past. This is where the concept of smart cities emerges as an ideal solution for tackling the challenges of urbanization. In this research, we began by identifying the most significant factors of integrated crisis management in smart cities with a focus on passive defense, with the importance of each factor further evaluated. The results were then analyzed.  In this work, data gathering was performed through a descriptive-analytic method based on library studies. The required qualitative data was collected by library studies by completing a checklist. Subsequently, numerical analyses were conducted using opinions from experts in the passive defense and smart cities studies. Afterward, an analytic hierarchical process (AHP) was utilized to appraise and rank different factors. Next, an adaptive neuro-fuzzy inference system (ANFIS) was coded in MATLAB R2021b, which ended up presenting an integrated model of crisis management in smart cities from the viewpoint of passive defense. Based on the AHP and ANFIS, our findings highlighted the importance of securing the Internet of things (IoT), securing the environment, securing the network, network acceptance control, developing visualization software at the level of operating system (container), suppressing the threats and modification, and the analysis and action-taking when it came to the integrated crisis management in smart cities from the viewpoint of passive defense. Considering the importance of building smart cities, it can be stipulated that comprehensive attention to integrated crisis management in smart cities considering the principles of passive defense can boost urban protection, security, and sustainable development. Therefore, we considered all important factors separately to come up with a final model. The presented model exhibited a final compatibility ratio of 0.059, which is pretty acceptable. Moreover, the trained ANFIS ended up with an RMSE of 0.0179 coupled with an R2 value of 0.9897, indicating the high accuracy of the proposed model.

کلیدواژه‌ها [English]

  • Crisis management
  • smart city
  • model presentation
  • ANFIS
  • passive defense

مراجع

[1] S. Farokhi Zadeh, M. Bagheri., H. Maleki Toulabi,. Investigation and Evaluation of Urban Water Distribution System in Terms of Passive Defense Using Fuzzy DEMATEL Technique, Disaster Prevention and Management Knowledge, 11(1) (2021) 67-80. (in Persian).
[2] M. Zolfaghari., S, Afrasiyabi., H, Sahami., Explaining the resilience indicators of the smart city and its role in the sustainable development of the city, in: The 2nd National Conference on the Conservation of Vital Infrastructure, Malek-Ashtar University of Technology, Iran, 2019, pp. 1-16. (in Persian).
[3] H. Vojdantabar, A, Motahari., H, Hoshangi., Investigating smart city infrastructure, in: The International Conference on Interdisciplinary Studies in Management and Engineering, Tehran University, Iran, 2019, pp. 1-14. (in Persian).
[4] J. Lee, H., Hancock, M., Toward a Framework for Smart Cities: A Comparison of Seoul, San Francisco and Amsterdam, in:  In Proceedings of Smart Green Cities Conference: Innovations for smart green cities: What’s working, what’s not, what’s next, Stanford Business School, Palo Alto: USA, 2012, pp. 1-7.
[5] K. Hamzeh, AM, Kazerooni., Smart cities: analysis of components, challenges and review of strategies, in: 3rd International Conference on Applied Researches in Structural Engineering and Construction Management, Sharif University of Technology, Iran, 2019, pp. 1-10. (in Persian).
[6] Z. Lv, D. Chen, J. Li., Novel system design and implementation for the smart city vertical market, IEEE Communications Magazine, 59(4) (2021) 126-131.
[7] M. Faraji Darbokhani, A. Afradiei, M. Samaninezhad, H. Shhinifar., Analysis and evaluation the dimensions of the smart city from point of view the Kermanshah citizens, Journal of Future Cities Vision, 4(2) (2023) 95-112. (in Persian).
[8] M. Samaninezhad, N. Khodakaramiyangilan., Meta-analysis of studies conducted in the field of smart city indicators in Iran, Rimag Journal, 73(19) (2023) 281-300. (in Persian).
[9] M. Kashef, A. Visvizi, O. Troisi., Smart city as a smart service system: Human-computer interaction and smart city surveillance systems, Computers in Human Behavior, 124 (2021) 106923.
[10] T. Nam, A. Pardo., Conceptualizing Smart City with Dimensions of Technology, People, and Institutions, 12th Annual International Conference on Digital Government Research, 2011, pp. 282-291.
[11] R. Dameri, C. Rosenthal-Sabroux., Smart city and value creation, edition1. Publisher Springer, Cham, 2014, pp. 1-12.
[12] M. Ghadimi, F, PadidaranMoghadam., Crisis management in smart city using expert system and wireless sensor networks, in: 2nd National conference on Computer Engineering and IT Management, Eshragh Institute of Higher Education, Iran, 2015, pp. 1-7. (in Persian).
[13] A. Farzadnia, D, MonsefiParapari., H, Sahami., The impact of smart cities on crisis management, a case study: Japan, in: Conference on Civil Engineering, Architecture and Urban Planning of the Islamic World, Shahid Beheshti University, Iran, 2018, pp. 1-10. (in Persian).
[14] M. Asgarirad, Nejati Jahromi, M., Techno-Economic Model of Sustainable Communication Infrastructure in the Smart City; using WDM-PON FTTx, Electronic and Cyber Defense, 9(1) (2021) 149-156. (in Persian).
[15] N. Sedighi, M, Sanaei., R, Ehteshamraei., A framework for assessing cyber security and privacy threats and investigating their impact on smart city performance, Scientific Journal of Electronical & Cyber Defence, 10(3) (2022) 77-91. (in Persian).
[16] P. Nakhirkan, et al., Identifying the Key Drivers of Smart City Development by Using the Combination of Meta-Synthesis and EDAS, Journal of Future Cities Vision, 4(2) (2023) 113-131. (in Persian).
[17] H. Ghasemi, E, Keshavartork., S, Mortazavi., M. Hadizadeh., Scenarios of smartening the city and policy making to realize the desirable scenario (case study: Qazvin city), Journal of Future Cities Vision, 4(2) (2023) 1-26. (in Persian).
[18] E. Khaliabasi, P, Pourmahmod., L, Rahimi., E. Karami., Presenting an infrastructure model for the development of Tabriz as a smart city, Journal of Safe City, 6(2) (2023) 67-82. (in Persian).
https://doi.org/10.22034/ispdrc.2023.2008946.1040
[19] M.e.a. Puentes, Towards Smart-City Implementation for Crisis Management in Fast-Growing and Unplanned Cities: The Colombian Scenario, Ingeniería Y Ciencia, 16(32) (2020) 151-169. https://doi.org/10.17230/ingciencia.16.32.7
[20] S.e.a. Rajkumar, Disaster Management in Smart Cities using IoT and Big Data, Journal of Physics: Conference Series, 1716(2020) (2020) 1-14. https://doi.org/10.1088/1742-6596/1716/1/012060
[21] M. Kollárová, Ristvej, J., Proposal of Risk Reduction Measures for the Construction of Smart Cities, in:  In Proceedings of the 14th International scientific conference on sustainable, modern and safe transport, Transportation Research Procedia, 2021, pp. 1753-1758. https://doi.org/10.1016/j.trpro.2021.07.194
[22] F.e.a. Zhao, Smart city research: A holistic and state-of-the-art literature review, Cities, 119 (2021) 1-14. https://doi.org/10.1016/j.cities.2021.103406
[23] R.e.a. Janani, IoT in smart cities: A contemporary survey, Global Transitions Proceedings, 2(2) (2021) 187-193. https://doi.org/10.1016/j.gltp.2021.08.069
[24] A.e.a. Visvizi, Smart city as a smart service system: Human-computer interaction and smart city surveillance systems, Computers in Human Behavior, 124 (2021) 1-14. https://doi.org/10.1016/j.chb.2021.106923
[25] L.e.a. Elvas, Disaster Management in Smart Cities, Smart Cities, 4(2) (2021) 819-832. https://doi.org/10.3390/smartcities4020042
[26] E.e.a. Gerasopoulos, Earth observation: An integral part of a smart and sustainable city, Environmental Science & Policy, 132 (2022) 296-307. https://doi.org/10.1016/j.envsci.2022.02.033
[27] R. Al Sharif, Pokharel, S, Smart City Dimensions and Associated Risks: Review of literature, Sustainable Cities and Society, 77 (2022) 1-14. https://doi.org/10.1016/j.scs.2021.103542
[28] S. Hosseini, Laali Niyat, I., Heidarinia, S., Analysis of the Pattern of Urban Smart Management, a New Way to Improve Urban Governance, Geographical Urban Planning Research, 7(4) (2019) 743-762. (in Persian). https://www.doi.org/10.22059/jurbangeo.2019.276474.1064
[29] SA. Hosseini, H. Maleki Toulabi., Examining an Appropriate Express Railway Pavement System Using Fuzzy DEMATEL Method, Journal of Transportation Research, Available Online from 22 October 2022 (2022). (in Persian). https://dx.doi.org/10.22034/tri.2022.329161.3018
 [30] G. Işıklar, Büyüközka, G., Using a multi-criteria decision making approach to evaluate mobile phone alternatives, Computer Standards & Interfaces, 29(2) (2007) 265-274. https://doi.org/10.1016/j.csi.2006.05.002
[31] M. Dağdeviren, Decision making in equipment selection: an integrated approach with AHP and PROMETHEE, Journal of Intelligent Manufacturing, 19 (2008) 397-406. https://doi.org/10.1007/s10845-008-0091-7
[32] J.-S.R. Jang, ANFIS: adaptive network based fuzzy inference system, IEEE Transactions on Systems, Man and Cybernetics, 23(3) (1993) 665-683. https://doi.org/10.1109/21.256541
[33] A. Azhdary Moghaddam, et al., Geometry Optimization of Triangle Labrinth Spillway Using ANFIS Models And Genetic Algorithms, Journal of Modeling in Engineering, 5(19) (2009) 57-68. (in Persian). https://dx.doi.org/10.22075/jme.2017.1547
[34] SA. Hosseini, H. Maleki Toulabi., Developing a Model of Estimating the Failure Rate for Main Urban Water Pipes Using Gene Expression Programming, Journal of Water and Wastewater Science and Engineering, 7(3) (2022) 28-43. (in Persian). https://dx.doi.org/10.22112/jwwse.2022.307076.1288
[35] C. Yang, Guofeng, Su., Jianguo, Chen, Using big data to enhance crisis response and disaster resilience for a smart city, in: In Proceedings of IEEE 2ndInternational Conference on Big Data Analysis (ICBDA), Beijing: China, 2017. https://doi.org/10.1109/ICBDA.2017.8078684
[36] D. Roostaei, Poormohamadi, D., Ghanbari, H., A theory of Smart Cities and Assessment its Infrastructure Components in Urban Management (Case Study: Tabriz Municipality), Geography and Territorial Spatial Arrangement, 8(26) (2018) 197-216. (in Persian). https://dx.doi.org/10.22111/gaij.2018.3634
[37] A. Ahmadpoor, and et al.,  Smart City: Explaining the needs and requirements of Tehran city for smartness, Journal of new attitudes in human geography, 10(2) (2018) 1-22. (in Persian).
[38] N. Bessis, Buildings and Crowds: Forming Smart Cities for More Effective Disaster Management, in:  In Proceedings of Fifth International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing, Seoul: South Korea, 2011, pp. 1-10. https://doi.org/10.1109/IMIS.2011.129
[39] A. Caraglui, Chiara, D.B. Nijkamp, Smart Cities in Europe, Journal of Urban Technology, 18(2) (2011) 45-59. https://doi.org/10.1080/10630732.2011.601117
[40] H. Jan, Vlasios, T., Catherne, M., Smart cities from machine to machine to the intimate of things, Kidlington: Oxford, Waltham, Langford Lane, 2014. https://doi.org/10.1016/C2017-0-04401-4
[41] M. Rahnama, Hayati, S., Analysis of Urban Smart Growth Indexes in Mashhad, Urban Structure and Function Studies, 1(4) (2013) 71-98. (in Persian).
 [42] N. Bansal, Mukherjee, M., Gairola, A., Plan to Gather Right Now Overall. From Vision to Reality for Vibrant Cities and Regions, in:  In Proceedings of 18th International Conference on Urban Planning, Regional Development and Information Society, Department of Architecture and planning: IIT Roorkee, 2017, pp. 1-10.
[43] N. Bozorgmehr, Habibi, M., Barakpour, N., Assessment of Karaj Current Development Plan Based on the Smart Growth, Journal of Architecture and Urban Planning, 6(11) (2013) 131-154. (in Persian). https://dx.doi.org/10.30480/aup.2013.115
[44] M. RazaviDehkordi, and et al., Investigation of problems and crisis management in smart cities, in: The 8nd International Conference on Sustainable Development, Urban Development and Reconstruction, Daneshpajoohan Institute of Higher Education, Iran, 2018, pp. 1-8. (in Persian).
[45] A. Vanolo, Smart mentality: The Smart City as Disciplinary Strategy, Urban Studies, 51(5) (2014) 883-898. https://doi.org/10.1177/0042098013494427
[46] C. Yang, Guofeng, Su., Jianguo, Chen, Using big data to enhance crisis response and disaster resilience for a smart city, in:  In Proceedings of IEEE 2ndInternational Conference on Big Data Analysis (ICBDA), Beijing: China, 2017. https://doi.org/10.1109/ICBDA.2017.8078684
[47] H.e.a. Chourabi, Understanding Smart Cities: An Integrative Framework, in:  In Proceedings of 45th Hawaii International Conference on System Sciences, Hawaii: USA, 2012, pp. 1-9. https://doi.org/10.1109/HICSS.2012.615
[48] C. Garau, Pavan, V.M,, Evaluating Urban Quality: Indicators and Assessment Tools for Smart Sustainable Cities, Sustainability, 10(3) (2018) 1-18. https://doi.org/10.3390/su10030575
نشریه مهندسی عمران امیرکبیر
دوره 55، شماره 11
بهمن 1402
صفحه 2227-2242

فایل ها

هم رسانی

ارجاع به این مقاله

آمار