| Machine learning techniques and data for stock market forecasting: A literature review MM Kumbure, C Lohrmann, P Luukka, J Porras Expert Systems with Applications 197, 116659, 2022 | 417 | 2022 |
| Global scenarios for significant water use reduction in thermal power plants based on cooling water demand estimation using satellite imagery A Lohrmann, J Farfan, U Caldera, C Lohrmann, C Breyer Nature Energy 4 (12), 1040-1048, 2019 | 120 | 2019 |
| Classification of intraday S&P500 returns with a Random Forest C Lohrmann, P Luukka International Journal of Forecasting 35 (1), 390-407, 2019 | 110 | 2019 |
| A combination of fuzzy similarity measures and fuzzy entropy measures for supervised feature selection C Lohrmann, P Luukka, M Jablonska-Sabuka, T Kauranne Expert Systems with Applications 110, 216-236, 2018 | 48 | 2018 |
| A novel similarity classifier with multiple ideal vectors based on k-means clustering C Lohrmann, P Luukka Decision Support Systems 111, 27-37, 2018 | 23 | 2018 |
| Global and regional models for identification of cooling technology in thermal power generation for water demand estimations in water-energy nexus studies A Lohrmann, C Lohrmann, P Luukka Journal of Cleaner Production 380, 134842, 2022 | 11 | 2022 |
| Troubled waters: Estimating the role of the power sector in future water scarcity crises A Lohrmann, J Farfan, C Lohrmann, JF Kölbel, F Pettersson Energy 282, 128820, 2023 | 7 | 2023 |
| Nonspecificity, strife and total uncertainty in supervised feature selection C Lohrmann, P Luukka Engineering Applications of Artificial Intelligence 109, 104628, 2022 | 7 | 2022 |
| Using clustering for supervised feature selection to detect relevant features C Lohrmann, P Luukka Machine Learning, Optimization, and Data Science: 5th International …, 2019 | 5 | 2019 |
| Supervised feature selection with a combination of fuzzy similarity measures and fuzzy entropy measures C Lohrmann, M Jablonska-Sabuka, T Kauranne, P Luukka Real Option Workshop, 19, 2018 | 5 | 2018 |
| A comparison of feature construction methods in the context of supervised feature selection for classification DD Nguyen, C Lohrmann, P Luukka International Conference on Green Technology and Sustainable Development, 48-59, 2022 | 3 | 2022 |
| A region-based approach for missing value imputation of cooling technologies for the global thermal power plant fleet using a decision tree classifier A Lohrmann, C Lohrmann, P Luukka Intelligent Systems and Applications in Business and Finance, 93-125, 2022 | 3 | 2022 |
| A Study on Relevant Features for Intraday S&P 500 Prediction Using a Hybrid Feature Selection Approach M Mailagaha Kumbure, C Lohrmann, P Luukka International Conference on Machine Learning, Optimization, and Data Science …, 2021 | 3 | 2021 |
| Fuzzy similarity and entropy (FSAE) feature selection revisited by using intra-class entropy and a normalized scaling factor C Lohrmann, P Luukka Intelligent Systems and Applications in Business and Finance, 61-92, 2022 | 2 | 2022 |
| Image based classification of shipments using transfer learning. M Leppioja, P Luukka, C Lohrmann KNOWCON, 37-44, 2021 | 2 | 2021 |
| Accuracy and Predictive Power of Sell-Side Target Prices for Global Clean Energy Companies C Lohrmann, A Lohrmann Sustainability 13 (22), 12746, 2021 | 1 | 2021 |
| Information transmission and nonspecificity in feature selection P Luukka, C Lohrmann Fuzzy Techniques: Theory and Applications: Proceedings of the 2019 Joint …, 2019 | 1 | 2019 |
| On the benefit of feature selection and ensemble feature selection for fuzzy k-nearest neighbor classification C Lohrmann, A Lohrmann, MM Kumbure Applied Soft Computing, 112784, 2025 | | 2025 |
| Author Correction: Global scenarios for significant water use reduction in thermal power plants based on cooling water demand estimation using satellite imagery A Lohrmann, J Farfan, U Caldera, C Lohrmann, C Breyer Nature Energy, 1-1, 2024 | | 2024 |
| Check for updates A Comparison of Feature Construction Methods in the Context of Supervised Feature Selection for Classification DD Nguyen, C Lohrmann, P Luukka Computational Intelligence Methods for Green Technology and Sustainable …, 2022 | | 2022 |
Pasi LuukkaProfessor, School of business and management, Lappeenranta University of TechnologyEmail verificata su lut.fi