Mina forskargrupper
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Data Intensive Software Technologies and Applications (DISTA) Forskargruppen Data Intensive Software Technologies and Applications studerar datastyrda metoder, såsom maskininlärning, artificiell…
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Linnaeus University Centre for Data Intensive Sciences and Applications DISA är Linnéuniversitetets spetsforskningsmiljö som arbetar med insamling, analys och nyttogörande av stora datamängder.…
Mina pågående forskningsprojekt
Publikationer
Artikel i tidskrift (Refereegranskat)
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Ghanadi, M., Kumar, M., Danielsson, P., Hultgren, G., Barsoum, Z. (2025). Unsupervised machine learning for local stress identification in fatigue analysis of welded joints. Welding in the World. 69. 213-226.
Status: Publicerad -
Kumar, M., Ekevid, T., Löwe, W. (2024). Operator model for wheel loader short-cycle loading handling. Automation in Construction. 167.
Status: Publicerad
Konferensbidrag (Refereegranskat)
- Cramsky, J., Kumar, M., Rieloff, E., Andersson, M., Danielsson, P.O., et al. (2026). Cross-Validation Comparison of Digital Twin Approaches Based on Simulated and Measured Road Roughness for Predicting Component Life in Articulated Haulers. Advances in Lean Manufacturing. 323-333.
- Kumar, M., Löwe, W., Cramsky, J., Danielsson, P. (2023). Driving pattern classification for wheel loaders in different material handling using machine learning. IEEE Transactions on Intelligent Transportation Systems, ITSC. 283-290.
- Kumar, M., Cramsky, J., Löwe, W., Danielsson, P. (2023). A prediction model for exhaust gas regeneration(EGR) clogging using offline and online machinelearning. Commercial Vehicle Technology 2022 : Proceedings of 7th commercial vehicle technology symposium.. 185-198.
Doktorsavhandling, sammanläggning (Övrigt vetenskapligt)
- Kumar, M. (2026). Digital Twin of Construction Equipment for Enhancing Performance. Doctoral Thesis. Växjö, 010 Publishers. 81.