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RAJABI Mohammadmahdi

ORCID
0000-0002-2181-6637
Main Referenced Co-authors
Al-Maktoumi, Ali (2)
Fahs, Marwan (2)
Hajibagheri, Zahra (2)
Rezaiezadeh Roukerd, Fatemeh (2)
BORDAS, Stéphane  (1)
Main Referenced Keywords
Convolutional neural network (2); Neural Networks, Computer (2); Neural-networks (2); Pollution (2); Water Science and Technology (2);
Main Referenced Disciplines
Civil engineering (4)
Mechanical engineering (2)

Publications (total 6)

The most downloaded
34 downloads
RAJABI, M., LAVIGNE, T., SUAREZ AFANADOR, C. A., BORDAS, S., Sbalzarini, I. F., & OBEIDAT, A. (2023). Physics-informed Dynamic Graph Convolutional Neural Network with Curriculum Learning for Pore-scale Flow Simulations. ORBilu-University of Luxembourg. https://orbilu.uni.lu/handle/10993/57127. https://hdl.handle.net/10993/57127

The most cited

20 citations (OpenAlex)

Virupaksha, A. G., Nagel, T., Lehmann, F., RAJABI, M., Hoteit, H., Fahs, M., & Le Ber, F. (May 2024). Modeling transient natural convection in heterogeneous porous media with Convolutional Neural Networks. International Journal of Heat and Mass Transfer, 222, 125149. doi:10.1016/j.ijheatmasstransfer.2023.125149 https://hdl.handle.net/10993/64372

Hajibagheri, Z., RAJABI, M., Oskouei, E. A., & Al-Maktoumi, A. (November 2024). Enhancing streamflow prediction in a mountainous watershed using a convolutional neural network with gridded data. Environmental Science and Pollution Research, 31 (55), 63959 - 63976. doi:10.1007/s11356-024-35482-1
Peer Reviewed verified by ORBi

Rezaiezadeh Roukerd, F., & RAJABI, M. (August 2024). Anomaly detection in groundwater monitoring data using LSTM-Autoencoder neural networks. Environmental Monitoring and Assessment, 196 (8). doi:10.1007/s10661-024-12848-z
Peer Reviewed verified by ORBi

Al-Maktoumi, A., RAJABI, M., Zekri, S., Govindan, R., Panjehfouladgaran, A., & Hajibagheri, Z. (June 2024). Accelerating regional-scale groundwater flow simulations with a hybrid deep neural network model incorporating mixed input types: A case study of the northeast Qatar aquifer. Journal of Hydroinformatics, 26 (6), 1333 - 1350. doi:10.2166/hydro.2024.275
Peer Reviewed verified by ORBi

Virupaksha, A. G., Nagel, T., Lehmann, F., RAJABI, M., Hoteit, H., Fahs, M., & Le Ber, F. (May 2024). Modeling transient natural convection in heterogeneous porous media with Convolutional Neural Networks. International Journal of Heat and Mass Transfer, 222, 125149. doi:10.1016/j.ijheatmasstransfer.2023.125149
Peer Reviewed verified by ORBi

Younes, A., RAJABI, M., Rezaiezadeh Roukerd, F., & Fahs, M. (March 2024). An Analytical Solution for Variable Viscosity Flow in Fractured Media: Development and Comparative Analysis With Numerical Simulations. Water Resources Research, 60 (3). doi:10.1029/2023WR035741
Peer Reviewed verified by ORBi

RAJABI, M., LAVIGNE, T., SUAREZ AFANADOR, C. A., BORDAS, S., Sbalzarini, I. F., & OBEIDAT, A. (2023). Physics-informed Dynamic Graph Convolutional Neural Network with Curriculum Learning for Pore-scale Flow Simulations. ORBilu-University of Luxembourg. https://orbilu.uni.lu/handle/10993/57127.

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