Network Communication and Electronic Control Strategy of New Energy Vehicles Based on Cloud Platform in the IoT Environment

Yufeng Tang

OAI: oai:igi-global.com:318135 • DOI: 10.4018/ijaci.318135

Aiming at the low accuracy of network intrusion detection (In-De) in the traditional network communication strategy of new energy vehicles (NEVs), this paper proposes an electronic control (E-C) strategy for network communication of NEVs based on cloud platform in the internet of things (IoT) environment. First, based on the cloud platform and deep learning (D-L) algorithm, the E-C system model including sensor, actuator, gateway, and cloud platform is constructed, and on this basis, the edge computing model is introduced to efficiently handle information interaction and computing tasks. Then, by using Bi-LSTM neural network to train historical data in the cloud center layer of the system, a D-L method combining cloud and edge nodes is proposed. Finally, by introducing the AlexNet network into the model, the problem of gradient vanishing when the network is deep is solved and the training speed is accelerated.

Artificial Intelligence Computer Science and Information Technology Artificial Intelligence