JETNET 3.0—A versatile artificial neural network package C Peterson, T Rögnvaldsson, L Lönnblad Computer Physics Communications 81 (1-2), 185-220, 1994 | 506 | 1994 |
Predicting the need for vehicle compressor repairs using maintenance records and logged vehicle data R Prytz, S Nowaczyk, T Rögnvaldsson, S Byttner Engineering applications of artificial intelligence 41, 139-150, 2015 | 201 | 2015 |
Using neural networks to identify jets L Lönnblad, C Peterson, T Rögnvaldsson Nuclear Physics B 349 (3), 675-702, 1991 | 195 | 1991 |
Pattern recognition in high energy physics with artificial neural networks—JETNET 2.0 L Lönnblad, C Peterson, T Rögnvalsson Computer Physics Communications 70 (1), 167-182, 1992 | 164 | 1992 |
Finding gluon jets with a neural trigger L Lönnblad, C Peterson, T Rögnvaldsson Physical review letters 65 (11), 1321, 1990 | 150 | 1990 |
An introduction to artificial neural networks C Peterson, TS Rögnvaldsson CERN, 1991 | 106 | 1991 |
Why neural networks should not be used for HIV-1 protease cleavage site prediction T Rögnvaldsson, L You Bioinformatics 20 (11), 1702-1709, 2004 | 102 | 2004 |
Modular, scriptable and automated analysis tools for high-throughput peptide mass fingerprinting J Samuelsson, D Dalevi, F Levander, T Rögnvaldsson Bioinformatics 20 (18), 3628-3635, 2004 | 101 | 2004 |
Transfer learning for remaining useful life prediction based on consensus self-organizing models Y Fan, S Nowaczyk, T Rögnvaldsson Reliability Engineering & System Safety 203, 107098, 2020 | 90 | 2020 |
Comprehensive bioinformatic analysis of the specificity of human immunodeficiency virus type 1 protease L You, D Garwicz, T Rognvaldsson Journal of virology 79 (19), 12477-12486, 2005 | 79 | 2005 |
Predicting System Loads with Artificial Neural Networks--Methods and Results from" The Great Energy Predictor Shootout" MBO Ohlsson, CO Peterson, H Pi, TS Rognvaldsson, BPW Soderberg ASHRAE Transactions-American Society of Heating Refrigerating …, 1994 | 78 | 1994 |
Smoothing regularizers for projective basis function networks J Moody, T Rögnvaldsson Advances in neural information processing systems 9, 1996 | 70 | 1996 |
On Langevin updating in multilayer perceptrons T Rögnvaldsson Neural computation 6 (5), 916-926, 1994 | 70 | 1994 |
Consensus self-organized models for fault detection (COSMO) S Byttner, T Rögnvaldsson, M Svensson Engineering applications of artificial intelligence 24 (5), 833-839, 2011 | 66 | 2011 |
Spark advance control using the ion current and neural soft sensors M Hellring, T Munther, T Rögnvaldsson, N Wickström, C Carlsson, ... SAE transactions, 1590-1595, 1999 | 54 | 1999 |
Automated methods for improved protein identification by peptide mass fingerprinting F Levander, T Rögnvaldsson, J Samuelsson, P James Proteomics 4 (9), 2594-2601, 2004 | 52 | 2004 |
Evaluation of self-organized approach for predicting compressor faults in a city bus fleet Y Fan, S Nowaczyk, T Rögnvaldsson Procedia Computer Science 53, 447-456, 2015 | 49 | 2015 |
Robust AFR estimation using the ion current and neural networks M Hellring, T Munther, T Rögnvaldsson, N Wickström, C Carlsson, ... SAE transactions, 1585-1589, 1999 | 46 | 1999 |
Self-monitoring for maintenance of vehicle fleets T Rögnvaldsson, S Nowaczyk, S Byttner, R Prytz, M Svensson Data mining and knowledge discovery 32, 344-384, 2018 | 44 | 2018 |
How to find simple and accurate rules for viral protease cleavage specificities T Rögnvaldsson, TA Etchells, L You, D Garwicz, I Jarman, PJG Lisboa BMC bioinformatics 10, 1-17, 2009 | 42 | 2009 |