A dynamic model for indoor temperature prediction in buildings P Hietaharju, M Ruusunen, K Leiviskä Energies 11 (6), 1477, 2018 | 57 | 2018 |
Data-driven framework for boiler performance monitoring RP Nikula, M Ruusunen, K Leiviskä Applied energy 183, 1374-1388, 2016 | 54 | 2016 |
Fuzzy modelling of carbon dioxide in a burning process M Ruusunen, K Leiviskä Control Engineering Practice 12 (5), 607-614, 2004 | 35 | 2004 |
Enabling demand side management: Heat demand forecasting at city level P Hietaharju, M Ruusunen, K Leiviskä Materials 12 (2), 202, 2019 | 22 | 2019 |
A stochastic dynamic building stock model for determining long-term district heating demand under future climate change P Hietaharju, J Pulkkinen, M Ruusunen, JN Louis Applied Energy 295, 116962, 2021 | 21 | 2021 |
Towards online adaptation of digital twins RP Nikula, M Paavola, M Ruusunen, J Keski-Rahkonen Open Engineering 10 (1), 776-783, 2020 | 16 | 2020 |
Fatigue prediction with intelligent stress indices based on torque measurements in a rolling mill E Juuso, M Ruusunen 10th International conference on condition monitoring and machinery failure …, 2013 | 15 | 2013 |
Mathematical analysis and update of ADM1 model for biomethane production by anaerobic digestion S Bertacchi, M Ruusunen, A Sorsa, A Sirviö, P Branduardi Fermentation 7 (4), 237, 2021 | 13 | 2021 |
Peak load cutting in district heating network P Hietaharju, M Ruusunen | 9 | 2018 |
Real-time moisture content monitoring of solid biomass in grate combustion M Ruusunen IFAC Proceedings Volumes 41 (2), 10652-10656, 2008 | 9 | 2008 |
Some change detection and time-series forecasting algorithms for an electronics manufacturing process M Paavola, M Ruusunen, M Pirttimaa University of Oulu, 2005 | 9 | 2005 |
A concept for cutting peak loads in district heating P Hietaharju, M Ruusunen Proceedings of the Automaatio XXI, Helsinki, Finland, 17-18, 2015 | 8 | 2015 |
Signal correlations in biomass combustion - an information theoretic analysis M Ruusunen Doctoral Thesis, 2013 | 8 | 2013 |
An attempt to find an empirical model between Barkhausen noise and stress A Sorsa, M Ruusunen, K Leiviskä, S Santa-Aho, M Vippola, T Lepistö Materials science forum 768, 209-216, 2014 | 7 | 2014 |
Linguistic equation models for failure mode identification from multisensor vibration analysis E Juuso, M Ruusunen, G Perigot Proceedings CM, 1408-1420, 2010 | 7 | 2010 |
Comparison of three change detection algorithms for an electronics manufacturing process M Ruusunen, M Paavola, M Pirttimaa, K Leiviska 2005 International Symposium on Computational Intelligence in Robotics and …, 2005 | 7 | 2005 |
Monitoring of small-scale biomass combustion processes. 28 p. March 2006 M Ruusunen ISBN 951-42-8028-8 (pdf), 0 | 7 | |
Estimation of wastewater flowrate in a gravitational sewer line based on a low-cost distance sensor J Tomperi, PM Rossi, M Ruusunen Water Practice & Technology 18 (1), 40-52, 2023 | 6 | 2023 |
Towards mineral beneficiation process chain intensification M Ohenoja, M Ruusunen, A Koistinen, J Kaartinen, J Paaso, A Isokangas, ... IFAC-PapersOnLine 51 (21), 201-206, 2018 | 6 | 2018 |
The effect of control parameters to the quality of small-scale wood pellet combustion M Ruusunen, T Korpela, T Björkqvist | 6 | 2009 |