Babak Mohammadi

E-postadressbabak.mohammadinateko.luse

Fingeravtryck

Utforska forskningsämnen där Babak Mohammadi är aktiv. Dessa ämnesetiketter kommer från personens arbeten. Tillsammans bildar de ett unikt fingeravtryck.

1 Liknande profiler

42 Artikel i vetenskaplig tidskrift
3 Debate/Note/Editorial
1 Översiktsartikel
1 Doktorsavhandling (sammanläggning)

Integrating machine learning with process-based glacio-hydrological model for improving the performance of runoff simulation in cold regions
Mohammadi, B., Gao, H., Pilesjö, P., Tuo, Y., Guo, R. & Duan, Z., 2025 feb. 24, I: Journal of Hydrology. 656, s. 132963
Forskningsoutput: Tidskriftsbidrag › Artikel i vetenskaplig tidskrift › Peer review

Öppen tillgång
An explainable hybrid framework for estimating daily reference evapotranspiration: Combining extreme gradient boosting with Nelder-Mead method
Mohammadi, B., Chen, M., Reza Nikoo, M., Cheraghalizadeh, M., Yu, Y., Zhang, H. & Yu, R., 2024 nov., I: Journal of Hydrology. 644, 132130.
Forskningsoutput: Tidskriftsbidrag › Artikel i vetenskaplig tidskrift › Peer review
Estimation of surface soil moisture from Sentinel-1 synthetic aperture radar imagery using machine learning method
Bulut, Ü., Mohammadi, B. & Duan, Z., 2024 nov., I: Remote Sensing Applications: Society and Environment. 36, 101369.
Forskningsoutput: Tidskriftsbidrag › Artikel i vetenskaplig tidskrift › Peer review

Öppen tillgång
Geostatistical Interpolation Approach for Improving Flood Simulation Within a Data-Scarce Region in the Tibetan Plateau
Guédé, K. G., Yu, Z., Hofmeister, F., Gu, H., Mohammadi, B., Chen, X., Lin, H., Shen, T. & Gouertoumbo, W. F., 2024 nov., I: Hydrological Processes. 38, 11, e15336.
Forskningsoutput: Tidskriftsbidrag › Artikel i vetenskaplig tidskrift › Peer review
Bee-inspired insights: Unleashing the potential of artificial bee colony optimized hybrid neural networks for enhanced groundwater level time series prediction
Katipoğlu, O. M., Mohammadi, B. & Keblouti, M., 2024 aug., I: Environmental Monitoring and Assessment. 196, 8, 724.
Forskningsoutput: Tidskriftsbidrag › Artikel i vetenskaplig tidskrift › Peer review

Improving hydrological modelling in cold regions using satellite remote sensing and machine learning techniques
Mohammadi, B. (Forskare), Duan, Z. (Handledare) & Pilesjö, P. (Biträdande handledare)
2021/01/01 → 2024/10/23
Projekt: Avhandling

Babak Mohammadi

Personlig profil

Fingeravtryck

Forskningsoutput

Integrating machine learning with process-based glacio-hydrological model for improving the performance of runoff simulation in cold regions

An explainable hybrid framework for estimating daily reference evapotranspiration: Combining extreme gradient boosting with Nelder-Mead method

Estimation of surface soil moisture from Sentinel-1 synthetic aperture radar imagery using machine learning method

Geostatistical Interpolation Approach for Improving Flood Simulation Within a Data-Scarce Region in the Tibetan Plateau

Bee-inspired insights: Unleashing the potential of artificial bee colony optimized hybrid neural networks for enhanced groundwater level time series prediction

Projekt

Improving hydrological modelling in cold regions using satellite remote sensing and machine learning techniques