桂林电子科技大学学报2025，Vol.45Issue(1)：62-68,7.DOI:10.16725/j.1673-808X.2024111
一种改进禁忌-BP神经网络的车载酒驾检测方法
An improved tabu-BP neural network for in-vehicle DUI detection
摘要
Abstract
For the problems of complex detection process,many influencing factors and low detection accuracy of traditional in-car DUI detection methods,an improved tabu search(TS)-BP neural network fusion in-car DUI detection method is proposed consider-ing the driver and passenger positions and open window areas.Firstly,the TS algorithm is improved by setting different domain ranges in each search phase;secondly,the initial weights and thresholds of the BP neural network are optimized using the improved algorithm to improve the efficiency and accuracy of the detection model and avoid falling into local optimal solutions;finally,the data from multiple sensors are fused to achieve high-precision in-car DUI detection.The experiments show that the proposed detection method improves 65.78%,88.20%and 58.38%of the model average absolute error,mean square error,and average absolute percentage error indexes,respectively,and the convergence speed and performance and robustness of the model are signifi-cantly improved compared with the traditional method.This study can provide a reference for in-vehicle portable DUI high-precision detection.关键词
交通安全/酒驾检测/禁忌搜索算法/多层前馈神经网络/多传感器融合Key words
traffic safety/DUI detection/tabu search algorithm/BP neural network/multi-sensor fusion分类
交通工程引用本文复制引用
毛棋良,赵红专,张鑫,覃月丽,刘志鹏..一种改进禁忌-BP神经网络的车载酒驾检测方法[J].桂林电子科技大学学报,2025,45(1):62-68,7.基金项目
广西重点研发计划(桂科AB21220052) （桂科AB21220052）
广西科技重大专项(桂科AA22068101) （桂科AA22068101）
柳州市重大专项(2021CAA0101) （2021CAA0101）
广西精密导航技术与应用重点实验开放课题(DH202225) （DH202225）
自治区级大学生创新创业训练计划(S202210595276) （S202210595276）
