| Sparse modeling approach for identifying the dominant factors affecting situation-dependent hourly electricity demand N Kaneko, Y Fujimoto, S Kabe, M Hayashida, Y Hayashi Applied energy 265, 114752, 2020 | 19 | 2020 |
| Machine learning approach for graphical model-based analysis of energy-aware growth control in plant factories Y Fujimoto, S Murakami, N Kaneko, H Fuchikami, T Hattori, Y Hayashi IEEE Access 7, 32183-32196, 2019 | 19 | 2019 |
| Sensitivity analysis of factors relevant to extreme imbalance between procurement plans and actual demand: Case study of the Japanese electricity market N Kaneko, Y Fujimoto, Y Hayashi Applied Energy 313, 118616, 2022 | 4 | 2022 |
| Graphical Modeling for Analysis of Hourly Electricity Demand and Market Price N Kaneko, Y Fujimoto, Y Hayashi 2020 17th International Conference on the European Energy Market (EEM), 1-6, 2020 | 3 | 2020 |
| Studies on Modeling Approaches for Analyzing Factors of Deviations Between Electricity Demand and its Procurement Plan N Kaneko 早稲田大学, 2023 | 1 | 2023 |
| Optimal Short-Term Charge/Discharge Operation for Electric Vehicles with Volt-Var Control in Day-Ahead Electricity Market H Kikusato, R Ando, J Hashimoto, K Otani, N Kaneko IEEE Open Access Journal of Power and Energy, 2024 | | 2024 |
| Model-based analysis to identify the impact of factors affecting electricity gaps during COVID-19: A case study in Germany N Kaneko, Y Fujimoto, HA Jacobsen, Y Hayashi Heliyon 10 (14), 2024 | | 2024 |
| Toward data-driven identification of essential factors causing seasonal change in daily electricity demand curves N Kaneko, Y Hayashi, Y Fujimoto 2019 IEEE Milan PowerTech, 1-6, 2019 | | 2019 |
