- حسین دوست، سمانه، زمانی، بهمن و فاطمی، افسانه. (1401). ارزیابی ابزارهای مدلسازی و شبیهسازی مبتنی بر عامل بر اساس استاندارد ایزو 25010. پژوهشهای نوین در تصمیمگیری، 7(1)، 61-86. https://sid.ir/paper/1045807/fa
- حقدوست، ع.، نوری حکمت، س.، طلایی، ب.، ملکپور افشار، ر.، صلواتی، ب.، بهزادی، ف.، بذرافشان، ع. (1401). بررسی عوامل مؤثر بر مهاجرت نیروی انسانی در حوزه سلامت در سال 1401. نشریه فرهنگ و ارتقای سلامت فرهنگستان علوم پزشکی، 6(2)، 205– http://dx.doi.org/10.22034/6.2.2
- رحمتی، ح. (1393). نقش مهاجرت سرمایههای فکری بر جریان دانش، پایاننامه کارشناسی ارشد، دانشگاه الزهرا (س).
- رصدخانه مهاجرت ایران. (1401). مهاجرت نیروی انسانی حوزه سلامت در جهان و ایران. در سالنامه مهاجرتی ایران ۱۴۰۱ (صص. ۳۶۶–۳۹۷). تهران: رصدخانه مهاجرت ایران. https://imobs.ir/outlook/detail/22
- صفاییپور، م. و محلی، ی. (۱۳۹۶). بررسی عوامل تأثیرگذار بر مهاجرت از شهر با استفاده از مدل معادلات ساختاری و تکنیک تحلیل سلسله مراتبی فازی (مطالعه موردی: شهر اهواز). مطالعات محیطی هفت حصار، ۶ (۲۲)، ۸۱-۹۶. http://hafthesar.iauh.ac.ir/article-1-500-fa.html
- علاءالدینی، فرشید، فاطمی، رزیتا، رنجبران جهرمی، هومن، اصغری رودسری، الهام، اسکندری، شروین، توکلی، حمیدرضا، رضوی، اوستا، فیض زاده، علی، حسین پور، احمدرضا، میرزاصادقی، علیرضا و اردلان، علی. (1384). میزان تمایل به مهاجرت و علل آن در پزشکان ایرانی. تحقیقات نظام سلامت حکیم (حکیم)، 8(3)، 9-15. https://sid.ir/paper/29245/fa
- غفاریان، ع.، فردوسی، م. (1401). مهاجرت کادر درمان؛ زنگ خطر به صدا درآمده است؟ مجله علمی دانشگاه علوم پزشکی بیرجند، 29(4)، 397– http://dx.doi.org/10.34785/bums024.2022.030
- فرتوک زاده، حمیدرضا و اشراقی، حسن. (1387). مدلسازی دینامیکی پدیده مهاجرت نخبگان و نقش نظام آموزش عالی در آن. پژوهش و برنامهریزی در آموزش عالی، 14(4 (50))، 139-168. https://sid.ir/paper/68087/fa
- فرحبخش، م.، مدیری، م.، خاتمی فیروزآبادی، س.م.ع.م.، پورابراهیمی، ع. (1401). شبیهسازی چرخه عمر صنعت برق با استفاده از شبیهسازی عاملبنیان. چشمانداز مدیریت صنعتی، 12(4)، 9– https://doi.org/10.52547/jimp.12.4.9
- ودادهیر، ابوعلی و اشراقی، سمیه. (1398). گرایش به مهاجرت به خارج در جامعه پزشکی ایران: مطالعهای کیفی. پژوهش و برنامهریزی در آموزش عالی، 25(2)، 23-42. https://sid.ir/paper/68063/fa
References
- Ale Ebrahim Dehkordi, M., Lechner, J. M., Ghorbani, A., Nikolic, I., Chappin, É., & Herder, P. M. (2023). Using machine learning for agent specifications in agent-based models and simulations: A critical review and guidelines. Journal of Artificial Societies and Social Simulation, 26(1). https://doi.org/10.18564/jasss.5016)
- Ali, H., Salleh, M., Talpur, K., Ullah, A., Ahmad, A., & Naseem, R. (2019). A review on data preprocessing methods for class imbalance problem. 390–397. https://doi.org/10.14419/ijet.v8i3.29508
- An, L., Grimm, V., Bai, Y., Sullivan, A., Turner, B. L. II, Malleson, N., Heppenstall, A., Vincenot, C., Robinson, D., Ye, X., Liu, J., Lindkvist, E., & Tang, W. (2023). Modeling agent decision and behavior in the light of data science and artificial intelligence. Environmental Modelling & Software, 166, 105713. https://doi.org/10.1016/j.envsoft.2023.105713
- Asadi, H., Ahmadi, B., Nejat, S., Akbari Sari, A., Garavand, A., Almasian Kia, A., & Hasoumi, M. (2018). Factors influencing the migration of Iranian healthcare professionals: A qualitative study. PloS ONE, 13(6), e0199613. https://doi.org/10.1371/journal.pone.0199613
- Badham, J., Chattoe-Brown, E., Gilbert, N., Chalabi, Z., Kee, F., & Ruth F. Hunter. (2018). Developing agent-based models of complex health behaviour. Health & Place, 54, 170-177. https://doi.org/10.1016/j.healthplace.2018.08.022
- Bandini, S., Manzoni, S., & Vizzari, G. (2009). Agent based modeling and simulation: An informatics perspective. Journal of Artificial Societies and Social Simulation, 12(4), 1–4. https://ideas.repec.org/a/jas/jasssj/2009-69-1.html
- Beyer, R. M., Schewe, J., & Abel, G. J. (2023). Modeling climate migration: dead ends and new avenues. Frontiers in Climate, 5(1212649). https://doi.org/10.3389/fclim.2023.1212649
- Bonabeau, B. (2002). Agent-based modeling: Methods and techniques for simulating human systems. PNAS, 99(suppl 3), 7280–7287. http://dx.doi.org/10.1073/pnas.082080899
- Carling, Jørgen (2011) The European Paradox of Unwanted Migration, in A Threat Against Europe? Security, Migration and Integration. Brussels: Brussels University Press (VUB) (33–46). https://www.prio.org/publications/31
- Chen, T., & Guestrin, C. (2016). XGBoost: A scalable tree boosting system. CoRR, abs/1603.02754. https://doi.org/10.1145/2939672.2939785
- Chen, Z., Jiang, S., Lu, M., & Sato, H. (2008). How do heterogeneous social interactions affect the peer effect in rural-urban migration?: Empirical evidence from China. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.1360689
- Connell, J. (2014). The two cultures of health worker migration: A Pacific perspective. Social Science & Medicine, 116, 73–81. https://doi.org/10.1016/j.socscimed.2014.06.043
- De Luca, G., Lampoltshammer, T. J., Parven, S., & Scholz, J. (2022). A literature review on the usage of agent-based modelling to study policies for managing international migration. Social Sciences, 11(8), 356. http://dx.doi.org/10.3390/socsci11080356
- Degfachew, T. N., Dilnesaw, M. M., & Massa, M. M. (2025). Impact of international labor migration on crop production in eastern Amhara, Ethiopia. A multinomial endogenous switching regression model analysis. Ecological Frontiers, 45(3), 768–779. https://doi.org/10.1016/j.ecofro.2025.02.004
- Di Caprio, D., Sironi, S., Lan, F.-Y., & Rostamkhani, R. (2025). A data-driven multicriteria decision model for healthcare workforce retention strategies. Healthcare Analytics (New York, N.Y.), 8(100403), 100403. https://doi.org/10.1016/j.health.2025.100403
- Dustmann, C., & Glitz, A. (2011). Migration and education. In E. A. Hanushek, S. Machin, & L. Woessmann (Eds.), Handbook of the Economics of Education (Vol. 4, pp. 327–434). Elsevier. https://doi.org/10.1016/B978-0-444-53444-6.00004-3
- Eaton, J., Baingana, F., Abdulaziz, M., Obindo, T., Skuse, D., & Jenkins, R. (2023). The negative impact of global health worker migration, and how it can be addressed. Public Health, 225, 254–257. https://doi.org/10.1016/j.puhe.2023.09.014
- Ehsani-Chimeh, E., Majdzadeh, R., Delavari, S., Najafi Gharebelagh, M., Rezaei, S., & Homaie Rad, E. (2018). Physicians’ retention rate and its effective factors in the Islamic Republic of Iran. East Mediterr Health J., 24(9), 830–837. https://doi.org/10.26719/2018.24.9.830
- Filatova, T., Verburg, P. H., Parker, D. C., & Stannard, C. A. (2013). Spatial agent-based models for socio-ecological systems: Challenges in design and validation. Environmental Modelling & Software, 45, 1–7. https://doi.org/10.1016/j.envsoft.2013.03.017
- Fu, Z., & Hao, L. (2018). Agent-based modeling of China’s rural–urban migration and social network structure. Physica A, 490, 1061–1075. https://doi.org/10.1016/j.physa.2017.08.145
- Ge, J., Polhill, J. G., Craig, T., & Liu, N. (2018). From oil wealth to green growth - An empirical agent-based model of recession, migration and sustainable urban transition. Environmental Modelling & Software, 107, 119–140. https://doi.org/10.1016/j.envsoft.2018.05.017
- Grebeniyk, A., Aleshkovski, I., & Maksimova, A. (2021). The impact of labor migration on human capital development. Migraciones Internacionales, 12, 0. https://doi.org/10.33679/rmi.v1i1.2190
- Grimm, V., Berger, U., Bastiansen, F., Eliassen, S., Ginot, V., Giske, J., & DeAngelis, D. L. (2006). A standard protocol for describing individual-based and agent-based models. Ecological Modelling, 198(1–2), 115–126. https://doi.org/10.1016/j.ecolmodel.2006.04.023
- Grimm, V., et al. (2020). The ODD protocol for describing agent-based and other simulation models: A second update to improve clarity, replication, and structural realism. Journal of Artificial Societies and Social Simulation, 23(2), 7. https://doi.org/10.18564/jasss.4259
- Gürsoy, F., & Badur, B. (2021). An agent-based modelling approach to brain drain. IEEE Transactions on Computational Social Systems. https://doi.org/10.1109/TCSS.2021.3066074
- Gutiérrez-López, A., González-Serrano, F.-J., & Figueiras-Vidal, A. R. (2023). Optimum Bayesian thresholds for rebalanced classification problems using class-switching ensembles. Pattern Recognition, 135, 109158. https://doi.org/10.1016/j.patcog.2022.109158
- Hamilton, R. I., & Papadopoulos, P. N. (2023). Using SHAP values and machine learning to understand trends in the transient stability limit. IEEE Transactions on Power Systems, 39(1), 1384–1397. https://doi.org/10.1109/tpwrs.2023.3248941
- Han, J., Guzman, J. A., & Chu, M. L. (2025). Prediction of gully erosion susceptibility through the lens of the SHapley Additive exPlanations (SHAP) method using a stacking ensemble model. Journal of Environmental Management, 383, 125478. https://doi.org/10.1016/j.jenvman.2025.125478
- Hassani-Mahmooei, B., & Parris, B. W. (2012). Climate change and internal migration patterns in Bangladesh: An agent-based model. Environment and Development Economics, 17(6), 763–780. https://doi.org/10.1017/S1355770X12000290
- Hinsch, M., & Bijak, J. (2019). Rumours lead to self-organized migration routes.
- Holmes, G. M., & Fraher, E. P. (2017). Developing physician migration estimates for workforce models. Health Services Research, 52, 529–545. https://doi.org/10.1111/1475-6773.12656
- James, G., Witten, D., Hastie, T., & Tibshirani, R. (2013). An Introduction to Statistical Learning (8th ed., Vol. 103). Springer New York. https://doi.org/10.1007/978-1-4614-7138-7
- Kazil, J., Masad, D., & Crooks, A. (2020). Utilizing python for agent-based modeling: The Mesa framework. In Lecture Notes in Computer Science. Social, Cultural, and Behavioral Modeling (pp. 308–317). https://doi.org/10.1007/978-3-030-61255-9_30
- Kennan, J., & Walker, J. R. (2013). Modeling individual migration decisions. In A. F. Constant & K. F. Zimmermann (Eds.), International handbook on the economics of migration (pp. 39–54). Edward Elgar Publishing.
- Khodabandelu, A., & Park, J. (2021). Agent-based modeling and simulation in construction. Automation in Construction, 131, 103882. https://doi.org/10.1016/j.autcon.2021.103882
- Klabunde, A., & Willekens, F. (2016). Decision-making in agent-based models of migration: State of the art and challenges. European Journal of Population, 32(1), 73–97. https://doi.org/10.1007/s10680-015-9362-0
- Kniveton, D., Smith, Ch., & Wood, Sh. (2011). Agent-based model simulations of future changes in migration flows for Burkina Faso. Global Environmental Change, 21(Supplement 1), S34–S40. https://doi.org/10.1016/j.gloenvcha.2011.09.006
- Lamperti, F., Roventini, A., & Sani, A. (2018). Agent-based model calibration using machine learning surrogates. Journal of Economic Dynamics & Control, 90, 366–389. https://doi.org/10.1016/j.jedc.2018.03.011
- Leitão, C. A., Salvador, G. L. de O., Idowu, B. M., & Dako, F. (2024). Drivers of global health care worker migration. Journal of the American College of Radiology, 21(8), 1188–1193. https://doi.org/10.1016/j.jacr.2024.03.005
- Lundberg, S. M., Erion, G., Chen, H., DeGrave, A., Prutkin, J. M., Nair, B., & Lee, S.-I. (2020). From local explanations to global understanding with explainable AI for trees. Nature Machine Intelligence, 2(1), 56–67. https://doi.org/10.1038/s42256-019-0138-9
- Marini, M., Chokani, N., & Abhari, R. S. (2019). Immigration and future housing needs in Switzerland: Agent-based modelling of agglomeration Lausanne. Computers, Environment and Urban Systems, 78, 101400. https://doi.org/10.1016/j.compenvurbsys.2019.101400
- Molnar, C., Freiesleben, T., König, G., Herbinger, J., Reisinger, T., Casalicchio, G., Wright, M. N., & Bischl, B. (2023). Relating the partial dependence plot and permutation feature importance to the data generating process. In L. Longo (Ed.), xAI 2023, CCIS 1901 (pp. 456–479). Springer, Cham https://doi.org/10.1007/978-3-031-44064-9_24
- Pratiwi, H., Windarto, A. P., Susliansyah, S., Aria, R. R., Susilowati, S., Rahayu, L. K., Fitriani, Y., Merdekawati, A., & Rahadjeng, I. R. (2020). Sigmoid Activation Function in Selecting the Best Model of Artificial Neural Networks. Journal of Physics: Conference Series, 1471(1), 012010. https://doi.org/10.1088/1742-6596/1471/1/012010
- Railsback, S. F., & Grimm, V. (2019). Agent-based and individual-based modeling (2nd edn). Princeton, NJ: Princeton University Press. ISBN: 9780691190822
- Raymer, J., Wiśniowski, A., Forster, J. J., Smith, P. W. F., & Bijak, J. (2013). Integrated modeling of European migration. Journal of the American Statistical Association, 108(503), 801–819. https://doi.org/10.1080/01621459.2013.789435
- Richey, M. K. (2020). Scalable Agent-Based Modeling of Forced Migration (Doctoral dissertation, George Mason University).
- Robinson, C., & Dilkina, B. (2018, June 20). A machine learning approach to modeling human migration. Proceedings of the 1st ACM SIGCAS Conference on Computing and Sustainable Societies, 1–8. Presented at the COMPASS ’18: ACM SIGCAS Conference on Computing and Sustainable Societies, Menlo Park and San Jose CA USA. https://doi.org/10.1145/3209811.3209868
- Salgado, M., & Gilbert, N. (2013). Agent based modelling. In Handbook of quantitative methods for educational research (pp. 247-265). Rotterdam: SensePublishers.
- Salle, I. L. (2015). Modeling expectations in agent-based models — An application to central bank’s communication and monetary policy. Economic Modelling, 46, 130–141. http://dx.doi.org/10.1016/j.econmod.2014.12.040
- Searle, C., & van Vuuren, J. H. (2021). Modelling forced migration: A framework for conflict-induced forced migration modelling according to an agent-based approach. Computers, Environment and Urban Systems, 85, 101568. https://doi.org/10.1016/j.compenvurbsys.2020.101568
- Silveira, J. J., Espíndola, A. L., & Penna, T. J. P. (2006). Agent-based model to rural–urban migration analysis. Physica A, 364, 445–456. doi:10.1016/j.physa.2005.08.055
- Simon, H. A. (1956). Rational Choice and the Structure of the Environment. Psychological Review, 63, 129-138. https://doi.org/10.1037/h0042769
- Taghikhah, F., Voinov, A., Filatova, T., & Polhill, J. G. (2022). Machine-assisted agent-based modeling: Opening the black box. Journal of Computational Science, 64, 101854. https://doi.org/10.1016/j.jocs.2022.101854
- Tah, J. H. M. (2005). Towards an agent-based construction supply network modelling and simulation platform. Automation in Construction, 14(3), 353–359. https://doi.org/10.1016/j.autcon.2004.08.003
- Taherahmadi, M., Khabaz Mafinejad, M., Sayarifard, A., Akbari Sari, A., & Farahani, P. (2023). Iranian medical students’ tendency to migrate and its associated factors. BMC Medical Education, 23(1), 232. https://doi.org/10.1186/s12909-023-04147-x
- Tolk, A., Diallo, S. Y., Turnitsa, C. D., & Yilmaz, L. (2022). Integrating machine learning with agent-based modeling: A methodological framework. Simulation Modelling Practice and Theory, 123, 102707. https://doi.org/10.1016/j.simpat.2022.102707
- Trinh, T. T., & Munro, A. (2023). Integrating a choice experiment into an agent-based model to simulate climate-change induced migration: The case of the Mekong River Delta, Vietnam. Journal of Choice Modelling, 48, 100428. https://doi.org/10.1016/j.jocm.2023.100428
- Turgut, Y., & Bozdag, C. E. (2023). A framework proposal for machine learning-driven agent-based models through a case study analysis. Simulation Modelling Practice and Theory, 123, 102707. https://doi.org/10.1016/j.simpat.2022.102707
- Valizadeh, S., Hasankhani, H., & Shojaeimotlagh, V. (2016). Nurses’ Immigration: Causes and Problems. IJMRHS, 5, 486–491.
- Van Dalen, H. P., & Henkens, K. (2013). Explaining emigration intentions and behaviour in the Netherlands, 2005-10. Population Studies, 67(2), 225–241. http://dx.doi.org/10.1080/00324728.2012.725135
- Van der Hoog, S. (2016). Deep learning in agent-based models: A prospectus. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.2711216
- Wilensky, U., & Rand, W. (2015). An introduction to agent-based modeling: Modeling natural, social, and engineered complex systems with NetLogo. MIT Press. https://mitpress.mit.edu/9780262731898/
- Wojtusiak, J., Warden, T., & Herzog, O. (2012). Machine learning in agent-based stochastic simulation: Inferential theory and evaluation in transportation logistics. Computers & Mathematics with Applications, 64(12), 3658–3665. https://doi.org/10.1016/j.camwa.2012.01.079
- Zhang, J., & Zhao, Z. (2026). Corporate ESG rating prediction based on XGBoost-SHAP interpretable machine learning model. Expert Systems With Applications, 295, 128809. https://doi.org/10.1016/j.eswa.2025.128809
- Zornić, N., & Marković, A. (2022). A methodological framework for the integration of machine learning algorithms into agent-based simulation models. Journal of Universal Computer Science: J. UCS, 28(5), 540–562. https://doi.org/10.3897/jucs.73924
References [In Persian]
- Ala Aldini, F., Fatemi, R., Ranjbaran Jahromi, H., Feyzzadeh, A., Ardalan, A., Hosseinpoor, A. R., Asghari Roudsari, E., Eskandari, Sh., Tavakoli, H. R., Mirzasadeghi, A. R., & Razavi, A. (2005). The inclination to immigration and the related factors among Iranian physicians. Hakim Research Journal, 8(3), 9–15. https://sid.ir/paper/29245/en
- Farahbakhsh, M., Modiri, M., Khatami Firozabadi, S. M. A., & Puorebrahimi, A. (2022). Power industry’s life cycle simulation using agent based modeling. Journal of Industrial Management Perspective, 12(4), 9–35. https://doi.org/10.52547/jimp.12.4.9
- Fartoukzadeh, H.R., & Eshraghi, H.. (2009). A Dynamic Modeling of Elites’ Immigration and the Role of Higher Education System. Journal of Research and Planning in Higher Education, 14(4 (50)), 139-168. SID. https://sid.ir/paper/68087/en
- Ghaffarian, A., & Ferdosi, M. (2022). Migration of medical staff; Has the alarm sounded? Journals of Birjand University of Medical Sciences, 29(4), 397–401. http://dx.doi.org/10.34785/bums024.2022.030
- Haghdoost, A. A., Noorihekmat, S., Talaei, B., Malekpour Afshar, R., Salavati, B., Behzadi, F., et al. (2022). An investigation of factors associated with emigration of the health workforce in Iran in 2022. Iranian Journal of Culture and Health Promotion, 6(2), 205–213. http://dx.doi.org/10.22034/6.2.2
- HoseinDoost, S., Zamani, B., & Fatemi, A. (2022). Evaluation of agent-based modeling and simulation tools based on ISO 25010. Modern Research in Decision Making, 7(1), 61–86. https://dor.isc.ac/dor/20.1001.1.24766291.1401.7.1.3.8
- Iran Migration Observatory. (2022). Human resources migration in the health sector in Iran and the world. In Iran Migration Outlook 2022 (pp. 366–397). Tehran: Iran Migration Observatory. https://imobs.ir/outlook/detail/22
- Rahmati, H. (2015). Role Of Intellectual Capitals Migration On The Knowledge Flow. M.SC.Thesis. Alzahra University.
- Safaie Pour, M., & Mahali, Y. (2017). Investigating Factors Affecting City Migration Using the Amos Structural Equation Modeling and Fuzzy Hierarchy Process Analysis (Case Study: Ahwaz City). Haft Hesar J Environ Stud 2018; 6 (22):81-96 http://hafthesar.iauh.ac.ir/article-1-500-fa.html
- Vedadhir, A., & Eshraghi, S. (2019). Attitude toward migrate abroad in Iranian medical community: A qualitative study. Journal of Research and Planning in Higher Education, 25(2), 23–42. https://sid.ir/paper/68063/en
استناد به این مقاله: خدادادادی، هما.، کاظمی، مصطفی.، مطهری فریمانی، ناصر.، طباطبائی، سید محمد. (1405). مدلسازی عاملبنیان مبتنی بر یادگیری ماشین: شبیهسازی تصمیم مهاجرت نیروهای انسانی بخش سلامت، مطالعات مدیریت کسب وکار هوشمند، 15(55)، 127-175. DOI: 10.22054/ims.2026.89993.2727
Journal of Business Intelligence Management Studies is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License..
|