American Psychological Association 6th edition

Chen, L., Wang, Z., Zhao, X., Shen, X., & He, W. (2024). A dynamic spectrum access algorithm based on deep reinforcement learning with novel multi-vehicle reward functions in cognitive vehicular networks. Telecommunication Systems: Modelling, Analysis, Design and Management, 87(2), 359-383. https://doi.org/10.1007/s11235-024-01188-5

ISO-690 (author-date, English)

CHEN, Lingling, WANG, Ziwei, ZHAO, Xiaohui, SHEN, Xuan und HE, Wei, 2024. A dynamic spectrum access algorithm based on deep reinforcement learning with novel multi-vehicle reward functions in cognitive vehicular networks. Telecommunication Systems: Modelling, Analysis, Design and Management. 1 Oktober 2024. Vol. 87, no. 2, p. 359-383. DOI 10.1007/s11235-024-01188-5.

Modern Language Association 9th edition

Chen, L., Z. Wang, X. Zhao, X. Shen, und W. He. „A Dynamic Spectrum Access Algorithm Based on Deep Reinforcement Learning With Novel Multi-Vehicle Reward Functions in Cognitive Vehicular Networks“. Telecommunication Systems: Modelling, Analysis, Design and Management, Bd. 87, Nr. 2, Oktober 2024, S. 359-83, https://doi.org/10.1007/s11235-024-01188-5.

Mohr Siebeck - Recht (Deutsch - Österreich)

Chen, Lingling/Wang, Ziwei/Zhao, Xiaohui/Shen, Xuan/He, Wei: A dynamic spectrum access algorithm based on deep reinforcement learning with novel multi-vehicle reward functions in cognitive vehicular networks, Telecommunication Systems: Modelling, Analysis, Design and Management 2024, 359-383.

Emerald - Harvard

Chen, L., Wang, Z., Zhao, X., Shen, X. und He, W. (2024), „A dynamic spectrum access algorithm based on deep reinforcement learning with novel multi-vehicle reward functions in cognitive vehicular networks“, Telecommunication Systems: Modelling, Analysis, Design and Management, Vol. 87 No. 2, S. 359-383.

Achtung: Diese Zitate sind unter Umständen nicht zu 100% korrekt.