Mohammed Safwan

1.

Mohammed, S., Arshad, S., Ocwa, A., Al-Dalahmeh, M., Aldabbas, A. K. A. E., Alzoubi, M. M., Vad, A., Harsányi, E.: Advanced attention-driven deep learning architectures for multi-depth soil temperature prediction.
Results in Engineering. 27, 1-17, (cikkazonosító: 106508), 2025.

doi DEA WoS Scopus

Folyóirat-mutatók:

D1 Engineering (miscellaneous)

2.

Ata, B., Pénzes, J., Pakrooh, P., Lotfata, A., Mohammed, S.: Comprehensive analysis of factors influencing EU-countries household energy consumption (2000-2022): Trends and vulnerability to COVID-19 and the Russia-Ukraine war.
Energy Strateg. Rev. 59, 1-21, (cikkazonosító: 101728), 2025.

doi DEA

Folyóirat-mutatók:

D1 Energy (miscellaneous)

3.

Mohammed, S., Raihan, A., Arshad, S., Ata, B., Ocwa, A., Al-Dalahmeh, M., Harsányi, E.: European Union agro-climate policies toward sustainability: analyzing emission trends and land use dynamics (1990-2021).
Resources, Environment and Sustainability. 21, 1-21, (cikkazonosító: 100239), 2025.

doi DEA Scopus

Folyóirat-mutatók:

D1 Environmental Engineering

D1 Environmental Science (miscellaneous)

D1 Management, Monitoring, Policy and Law

D1 Pollution

4.

Vicente-Serrano, S. M., Mohammed, S., Potopová, V.: High temporal variability not trend dominates Mediterranean precipitation.
Nature. 639 (8055), 658-666, 2025.

doi DEA WoS Scopus

Folyóirat-mutatók:

D1 Multidisciplinary

5.

Mohammed, S.: Modeling Current and Future Run-off and Soil Erosion Dynamics in Eastern Mediterranean Ecosystems Using the WEPP Model.
Energy Nexus. 17, 1-13, (cikkazonosító: 100375), 2025.

doi DEA

Folyóirat-mutatók:

Q1 Energy (miscellaneous)

D1 Environmental Science (miscellaneous)

6.

Arshad, S., Kazmi, J. H., Harsányi, E., Nazli, F., Hassan, W., Shaikh, S., Al-Dalahmeh, M., Mohammed, S.: Predictive Modeling of soil salinity integrating remote sensing and soil variables: An ensembled deep learning approach.
Energy Nexus. 17, 1-22, (cikkazonosító: 100374), 2025.

doi DEA

Folyóirat-mutatók:

Q1 Energy (miscellaneous)

D1 Environmental Science (miscellaneous)

7.

Nyéki, A., Tarek, A., Arshad, S., Gombkötő, N., Neményi, M., Mirzaei, M., Szabó, S., Harsányi, E., Al-Dalahmeh, M., Mohammed, S.: Real-time monitoring of ammonia emissions from cereal crops using LoRaWAN-based sensing technology.
Sci Rep. 16 (1), 1-28, (cikkazonosító: 1446), 2025.

doi DEA

Folyóirat-mutatók:

Q1 Multidisciplinary

8.

Fejér, P., Széles, A., Nagy, J., Ragán, P., Juhász, C., Mohammed, S., Rátonyi, T.: A kukorica keményítőtartalmának előrejelzése mesterséges neurális hálózatok (ANN) segítségével.

DEA

9.

Altouma, A., Bashir, B., Ata, B., Ocwa, A., Alsalman, A., Harsányi, E., Mohammed, S.: An environmental impact assessment of Saudi Arabia's vision 2030 for sustainable urban development: a policy perspective on greenhouse gas emissions.
Environ Sustain Indic. 21, 1-13, (cikkazonosító: 100323), 2024.

doi DEA WoS Scopus

Folyóirat-mutatók:

D1 Agricultural and Biological Sciences (miscellaneous)

D1 Ecology, Evolution, Behavior and Systematics

Q1 Environmental Science (miscellaneous)

Q1 Management, Monitoring, Policy and Law

10.

Harsányi, E., Mirzaei, M., Arshad, S., Alsilibe, F., Vad, A., Nagy, A. S., Rátonyi, T., Gorkom, G. V., Al-Dalahmeh, M., Mohammed, S.: Assessment of Advanced Machine and Deep Learning Approaches for Predicting CO2 Emissions from Agricultural Lands: Insights Across Diverse Agroclimatic Zones.
Earth Syst. Environ. 8 (4), 1109-1125, 2024.

doi DEA WoS Scopus

Folyóirat-mutatók:

D1 Computers in Earth Sciences

Q1 Economic Geology

Q1 Environmental Science (miscellaneous)

D1 Geology

Q1 Global and Planetary Change

11.

Mohammed, S., Gill, A. R., Ghosal, K., Al-Dalahmeh, M., Alsafadi, K., Szabó, S., Oláh, J., Alkerdi, A., Ocwa, A., Harsányi, E.: Assessment of the environmental kuznets curve within EU-27: Steps toward environmental sustainability (1990-2019).
Env. Sci. Ecotechnol. 18, 1-13, (cikkazonosító: 100312), 2024.

doi DEA WoS Scopus

Folyóirat-mutatók:

D1 Ecology

D1 Environmental Engineering

D1 Environmental Science (miscellaneous)

12.

Mohammed, S., Arshad, S., Bashir, B., Ata, B., Al-Dalahmeh, M., Alsalman, A., Ali, H., Alhennawi, S., Kiwan, S., Harsányi, E.: Evaluating machine learning performance in predicting sodium adsorption ratio for sustainable soil-water management in the eastern Mediterranean.
J. Environ. Manage. 370, 1-14, (cikkazonosító: 122640), 2024.

doi DEA WoS Scopus

Folyóirat-mutatók:

D1 Environmental Engineering

D1 Management, Monitoring, Policy and Law

D1 Medicine (miscellaneous)

D1 Waste Management and Disposal

13.

Letswamotse, T. V., Arshad, S., Bashir, B., Alsalman, A., Harsányi, E., Al-Dalahmeh, M., Mohammed, S.: Integrating Maize Yield and Agricultural Drought Analysis for Sustainable Food Security: A Provincial Study in South Africa (1993-2022).
Food and Energy Security. 13 (5), 1-20, (cikkazonosító: 70006), 2024.

doi DEA WoS Scopus

Folyóirat-mutatók:

D1 Agronomy and Crop Science

Q1 Food Science

D1 Forestry

Q2 Renewable Energy, Sustainability and the Environment

14.

Mohammed, S., Arshad, S., Bashir, B., Vad, A., Alsalman, A., Harsányi, E.: Machine learning driven forecasts of agricultural water quality from rainfall ionic characteristics in Central Europe.
Agric. Water Manage. 293, 1-15, (cikkazonosító: 108690), 2024.

doi DEA WoS Scopus

Folyóirat-mutatók:

D1 Agronomy and Crop Science

D1 Earth-Surface Processes

D1 Soil Science

D1 Water Science and Technology

15.

Ocwa, A., Mohammed, S., Mousavi, S. M. N., Illés, Á., Bojtor, C., Ragán, P., Rátonyi, T., Harsányi, E.: Maize Grain Yield and Quality Improvement Through Biostimulant Application: a Systematic Review.
J Soil Sci Plant Nutr. 24, 1609-1649, 2024.

doi DEA WoS Scopus

Folyóirat-mutatók:

Q1 Agronomy and Crop Science

Q1 Plant Science

Q2 Soil Science

16.

Széles, A., Huzsvai, L., Mohammed, S., Nyéki, A., Zagyi, P., Horváth, É., Simon, K., Arshad, S., Tamás, A.: Precision agricultural technology for advanced monitoring of maize yield under different fertilization and irrigation regimes: a case study in Eastern Hungary (Debrecen).
J. Agric. Food Res. 15, 1-16, (cikkazonosító: 100967), 2024.

doi DEA WoS Scopus

Folyóirat-mutatók:

Q1 Agricultural and Biological Sciences (miscellaneous)

Q1 Agronomy and Crop Science

Q1 Food Science

17.

Faheem, Z., Kazmi, J. H., Shaikh, S., Arshad, S., Mohammed, S.: Random forest-based analysis of land cover/land use LCLU dynamics associated with meteorological droughts in the desert ecosystem of Pakistan.
Ecol. Indic. 159, 1-20, (cikkazonosító: 111670), 2024.

doi DEA WoS Scopus

Folyóirat-mutatók:

D1 Decision Sciences (miscellaneous)

D1 Ecology

D1 Ecology, Evolution, Behavior and Systematics

18.

Alsafadi, K., Bashir, B., Mohammed, S., Abdo, H. G., Mokhtar, A., Alsalman, A., Cao, W.: Response of Ecosystem Carbon-Water Fluxes to ExtremeDrought in West Asia.
Remote Sens. 16 (7), 1-27, (cikkazonosító: 1179), 2024.

doi DEA WoS Scopus

Folyóirat-mutatók:

Q1 Earth and Planetary Sciences (miscellaneous)

19.

Mohammed, S., Arshad, S., Alsilibe, F., Moazzam, M. F. U., Bashir, B., Prodhan, F. A., Alsalman, A., Vad, A., Rátonyi, T., Harsányi, E.: Utilizing machine learning and CMIP6 projections for short-term agricultural drought monitoring in central Europe (1900-2100).
J. Hydrol. 633, 1-21, (cikkazonosító: 130968), 2024.

doi DEA WoS Scopus

Folyóirat-mutatók:

D1 Water Science and Technology

20.

Ocwa, A., Harsányi, E., Széles, A., Holb, I., Szabó, S., Rátonyi, T., Mohammed, S.: A bibliographic review of climate change and fertilization as the main drivers of maize yield: implications for food security.
Agric & Food Secur. 12 (1), 1-18, (cikkazonosító: 14), 2023.

doi DEA WoS Scopus

Folyóirat-mutatók:

Q1 Agronomy and Crop Science

Q1 Ecology

Q1 Food Science

21.

Arshad, S., Kazmi, J. H., Javed, M. G., Mohammed, S.: Applicability of machine learning techniques in predicting wheat yield based on remote sensing and climate data in Pakistan, South Asia.
Eur. J. Agron. 147, 1-19, (cikkazonosító: 126837), 2023.

doi DEA WoS Scopus

Folyóirat-mutatók:

D1 Agronomy and Crop Science

D1 Plant Science

Q1 Soil Science

22.

Mirzaei, M., Anari, M. G., Diaz, P. E., Saronjic, N., Mohammed, S., Szabó, S., Mousavi, S. M. N., Caballero-Calvo, A.: Assessment of soil CO2 and NO fluxes in a semi-arid region using machine learning approaches.
J. Arid. Environ. 211, 1-9, (cikkazonosító: 104947), 2023.

doi DEA WoS Scopus

Folyóirat-mutatók:

Q1 Earth-Surface Processes

Q1 Ecology

Q2 Ecology, Evolution, Behavior and Systematics

23.

Harsányi, E., Bashir, B., Arshad, S., Ocwa, A., Vad, A., Alsalman, A., Bácskai, I., Rátonyi, T., Hijazi, O., Széles, A., Mohammed, S.: Data Mining and Machine Learning Algorithms for Optimizing Maize Yield Forecasting in Central Europe.
Agronomy-Basel. 13 (5), 1-22, (cikkazonosító: 1297), 2023.

doi DEA WoS Scopus

Folyóirat-mutatók:

Q1 Agronomy and Crop Science

24.

Mirzaei, M., Anari, M. G., Saronjic, N., Sarkar, S., Kral, I., Gronauer, A., Mohammed, S., Caballero-Calvo, A.: Environmental impacts of corn silage production: influence of wheat residues under contrasting tillage management types.
Environ. Monit. Assess. 195 (1), 1-20, (cikkazonosító: 171), 2023.

doi DEA WoS Scopus

Folyóirat-mutatók:

Q2 Environmental Science (miscellaneous)

Q2 Management, Monitoring, Policy and Law

Q2 Medicine (miscellaneous)

Q2 Pollution

25.

Alsafadi, K., Bi, S., Mokhtar, A., Abdo, H. G., He, H., Mohammed, S.: Evaluation of an Evapotranspiration Deficit-Based Drought Index and Its Impacts on Carbon Productivity in the Levant and Iraq.
In: , CRC Press, Boca Raton(USA), , 2023. ISBN: 9781003276555(ebook)

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Mohammed Safwan

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