Mohammad Aslani
Universitetsadjunkt i datavetenskap
E-post: mohammad.aslani@hig.se
Telefon: 026-64 85 66
Mohammad Aslani has built his academic career on a solid foundation in geoinformatics and artificial intelligence. His research is mainly centered around intelligent geoinformatics, the amalgamation of geoinformatics and artificial intelligence. His research focuses on methodological development around multi-agent systems, machine learning, and data analysis to support various GIS applications. Specifically, he is interested in developing methods based on fuzzy logic, neural networks, reinforcement learning, deep learning, multi-agent systems, and evolutionary optimization for urban-related applications.
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Senaste publikationerna
Abad, S., Gholamy, H. & Aslani, M. (2023). Classification of Malicious URLs Using Machine Learning. Sensors, 23 (18). 10.3390/s23187760
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Safia, M., Abbas, R. & Aslani, M. (2023). Classification of Weather Conditions Based on Supervised Learning for Swedish Cities. Atmosphere, 14 (7). 10.3390/atmos14071174
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Aslani, M. & Seipel, S. (2023). Rooftop segmentation and optimization of photovoltaic panel layouts in digital surface models. Computers, Environment and Urban Systems, 105. 10.1016/j.compenvurbsys.2023.102026
[Mer information]
Aslani, M. & Seipel, S. (2023). Solar Energy Assessment: From Rooftop Extraction to Identifying Utilizable Areas. Geographical Information Systems Theory, Applications and Management, 7th International Conference, GISTAM 2021, Virtual Event, April 23–25, 2021, and 8th International Conference, GISTAM 2022, Virtual Event, April 27-29, 2022, Revised Selected Papers: Springer. S. 102-115. 10.1007/978-3-031-44112-7_7
[Mer information]
Aslani, M. & Seipel, S. (2022). A Spatially Detailed Approach to the Assessment of Rooftop Solar Energy Potential based on LiDAR Data. Proceedings of the 8th International Conference on Geographical Information Systems Theory, Applications and Management - GISTAM: ScitePress. S. 56-63. 10.5220/0011108300003185
[Mer information]