| Abstract:In the field of vehicle autonomous driving, there are many types of operating status data, with obvious feature fuzziness and difficulty in accurately collecting, which leads to problems such as low accuracy, low accuracy, and slow time efficiency in vehicle operating status monitoring. Therefore, a multi-dimensional intelligent monitoring method for vehicle operation status based on fuzzy neural network is proposed. Firstly, vehicle operating status data is collected through multiple sensors, and the collected data is fused using an adaptive weighted average algorithm. Secondly, by using adaptive genetic algorithm and floating search algorithm, the optimal feature subset of vehicle operating state multi fusion data is obtained. Finally, the optimal feature subset of vehicle operation status is input into the fuzzy neural network model to complete multi-dimensional intelligent monitoring of vehicle operation status. The experimental results show that the proposed method can achieve accurate monitoring of four vehicle operating states: deceleration, normal, acceleration, and anti hunting, and has high monitoring efficiency for vehicle operating states, making it suitable for practical applications. |
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