BORNEO, ANGELO
BORNEO, ANGELO
Dipartimento Energia
091283
Mostra
records
Risultati 1 - 1 di 1 (tempo di esecuzione: 0.002 secondi).
Citazione | Data di pubblicazione | Autori | File |
---|---|---|---|
Acceleration control strategy for Battery Electric Vehicle based on Deep Reinforcement Learning in V2V driving / Acquarone, Matteo; Borneo, Angelo; Misul, Daniela Anna. - ELETTRONICO. - (2022), pp. 202-207. (Intervento presentato al convegno 2022 IEEE Transportation Electrification Conference and Expo, ITEC 2022 tenutosi a Anaheim, CA, USA nel 15-17 June 2022) [10.1109/ITEC53557.2022.9813785]. | 1-gen-2022 | Acquarone, MatteoBorneo, AngeloMisul, Daniela Anna | Acceleration_control_strategy_for_Battery_Electric_Vehicle_based_on_Deep_Reinforcement_Learning_in_V2V_driving.pdf; Acceleration_control_strategy_for_Battery_Electric_Vehicle_based_on_Deep_Reinforcement_Learning_in_V2V_driving_.pdf |