Dr. Morteza Pakdaman
Research Institute of Meteorology and Atmospheric Sciences (RIMAS)
Climate Research Institute (CRI), Mashhad, Iran
Assistant Professor
Email: pakdaman.m@gmail.com
Qualifications
2014 Ph.D., Ferdowsi University of Mashhad, Mashahd, Iran
Publications (Selected)
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Pakdaman, M., & Kouhi, M. (2025). Computational decision intelligence approaches for drought prediction: A review. Uncertainty in Computational Intelligence-Based Decision Making, 119-131.
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Asadi Oskouei, E., Pakdaman, M., Falamarzi, Y., & Javanshiri, Z. (2024). A hybrid approach for generating daily 2m temperature of 1km spatial resolution over Iran. Theoretical and Applied Climatology, 1-11.
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Pakdaman, M., Fattahi, E., & Javanshiri, Z. (2024). Forecasting the average monthly rainfall in the northwest of Iran using teleconnections and machine learning. Iranian Journal of Geophysics, 18(2), 77-90.
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Frassoni, A., Reynolds, C., Wedi, N., Bouallègue, Z. B., Caltabiano, A. C. V., Pakdaman, M., ... & Zängl, G. (2023). Systematic errors in weather and climate models: Challenges and opportunities in complex coupled modeling systems. Bulletin of the American Meteorological Society, 104(9), E1687-E1693.
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Ezzati, S., Zenner, E. K., Pakdaman, M., Naseri, M. H., Nikjoui, M., & Ahmadi, S. (2023). Spatially explicit modeling of disease surveillance in mixed oak-hardwood forests based on machine-learning algorithms. Journal of Environmental Management, 337, 117714.
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Shloof, A. M., Senu, N., Ahmadian, A., Pakdaman, M., & Salahshour, S. (2023). A new iterative technique for solving fractal-fractional differential equations based on artificial neural network in the new generalized Caputo sense. Engineering with Computers, 39(1), 505-515.
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Javanshiri, Z., Babaeian, I., & Pakdaman, M. (2023). Influence of large-scale climate signals on the precipitation variability over Iran. Stochastic Environmental Research and Risk Assessment, 37(5), 1745-1762.
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Raza, A., Ahmadian, A., Rafiq, M., Ang, M. C., Salahshour, S., & Pakdaman, M. (2022). The impact of delay strategies on the dynamics of coronavirus pandemic model with nonlinear incidence rate. Fractals, 30(05), 2240121.
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Pakdaman, M., Babaeian, I., & Bouwer, L. M. (2022). Improved monthly and seasonal multi-model ensemble precipitation forecasts in southwest asia using machine learning algorithms. Water, 14(17), 2632.
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Oliazadeh, A., Bozorg-Haddad, O., Pakdaman, M., Baghbani, R., & Loáiciga, H. A. (2022). Optimal merging of multi-satellite precipitation data in urban areas. Theoretical and Applied Climatology, 147(3), 1697-1712.
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Pakdaman, M., Babaeian, I., Javanshiri, Z., & Falamarzi, Y. (2022). European multi model ensemble (emme): a new approach for monthly forecast of precipitation. Water Resources Management, 36(2), 611-623.
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Javanshiri, Z., Pakdaman, M., & Falamarzi, Y. (2021). Homogenization and trend detection of temperature in Iran for the period 1960–2018. Meteorology and Atmospheric Physics, 133, 1233-1250.
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Pooya, A., & Pakdaman, M. (2021). A new continuous time optimal control model for manpower planning with promotion from inside the system. Operational Research, 21(1), 349-364.
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Pakdaman, M., Naghab, S. S., Khazanedari, L., Malbousi, S., & Falamarzi, Y. (2020). Lightning prediction using an ensemble learning approach for northeast of Iran. Journal of Atmospheric and Solar-Terrestrial Physics, 209, 105417.
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Pakdaman, M., Falamarzi, Y., Yazdi, H. S., Ahmadian, A., Salahshour, S., & Ferrara, M. (2020). A kernel least mean square algorithm for fuzzy differential equations and its application in earth’s energy balance model and climate. Alexandria Engineering Journal, 59(4), 2803-2810.
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Pooya, A., & Pakdaman, M. (2019). Optimal control model for finite capacity continuous MRP with deteriorating items. Journal of Intelligent Manufacturing, 30, 2203-2215.
Profile Details
https://orcid.org/0000-0002-8656-9251
https://scholar.google.com/citations?user=BqjygGYAAAAJ&hl=en
https://www.researchgate.net/profile/Morteza-Pakdaman
WoS ResearcherID: T-8502-2019