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Using Dynamic Neural Networks for Battery State of Charge Estimation in Electric Vehicles.

, , , , and . ANT/SEIT, volume 130 of Procedia Computer Science, page 533-540. Elsevier, (2018)

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Speed Optimisation Module of a Hydraulic Francis turbine based on Artificial Neural Networks. Application to the Dynamic Analysis and Control of an Adjustable Speed Hydro Plant., , , , and . IJCNN, page 4104-4110. IEEE, (2006)Design and comparison of adaptive power system stabilizers based on neural fuzzy networks and genetic algorithms., and . Neurocomputing, 70 (16-18): 2902-2912 (2007)Dam seepage analysis based on artificial neural networks: The hysteresis phenomenon., , and . IJCNN, page 1-8. IEEE, (2013)A Guide to Data Collection for Computation and Monitoring of Node Energy Consumption., , , , , and . Big Data Cogn. Comput., 7 (3): 130 (2023)Development of an Integrated Virtual-Remote Lab for Teaching Induction Motor Starting Methods., , , and . Rev. Iberoam. de Tecnol. del Aprendiz., 8 (2): 77-81 (2013)Vehicle to vehicle energy exchange in smart grid applications., , , , and . ICCVE, page 178-184. IEEE, (2014)Preface., and . FNC/MobiSPC, volume 175 of Procedia Computer Science, page 6-7. Elsevier, (2020)Using Dynamic Neural Networks for Battery State of Charge Estimation in Electric Vehicles., , , , and . ANT/SEIT, volume 130 of Procedia Computer Science, page 533-540. Elsevier, (2018)Feasibility Study of an Electric Shuttle Fleet Fed by Solar Power., , and . ANT/SEIT, volume 83 of Procedia Computer Science, page 799-806. Elsevier, (2016)Charge scheduling strategies for managing an electric vehicle fleet parking., and . EUROCON, page 1-6. IEEE, (2015)