| 减法聚类和粒子群优化TS模糊神经网络的驾驶疲劳融合检测(英文) |
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| 引用本文： | 孙伟,张为公,李旭,陈刚.减法聚类和粒子群优化TS模糊神经网络的驾驶疲劳融合检测(英文)[J].东南大学学报,2009,25(3):356-361. |
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| 作者姓名： | 孙伟 张为公 李旭 陈刚 |
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| 作者单位： | 东南大学仪器科学与工程学院,南京,210096 |
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| 基金项目： | The National Key Technologies R&D Program during the 11th Five-Year Plan Period，the Ph.D. Programs Foundation of Ministry of Education of China，the Transportation Science Research Project of Jiangsu Province |
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| 摘 要： | 为提高基于单一特征检测算法的准确率和可靠性,提出基于多个特征的驾驶疲劳融合检测算法.从直接反映驾驶员疲劳的2个面部特征和间接反映疲劳的1个车辆行为特征2个方面对驾驶疲劳进行综合检测.该算法运用TS模糊神经网络来识别驾驶疲劳,采用减法聚类对网络进行结构辨识,确定模糊规则的条数及相关参数的初始值,并改进了粒子群优化算法对网络进行训练.仿真和实车实验表明,该算法不仅能有效改善TS模糊神经网络的收敛速度和识别精度,而且能提高驾驶疲劳的检测正确率.
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| 关 键 词： | 驾驶疲劳 融合检测 粒子群优化 减法聚类 |
Driving fatigue fusion detection based on T-S fuzzy neural network evolved by subtractive clustering and particle swarm optimization |
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| Sun Wei Zhang Weigong Li Xu Chen Gang.Driving fatigue fusion detection based on T-S fuzzy neural network evolved by subtractive clustering and particle swarm optimization[J].Journal of Southeast University(English Edition),2009,25(3):356-361. |
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| Authors: | Sun Wei Zhang Weigong Li Xu Chen Gang |
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| Institution: | Sun Wei Zhang Weigong Li Xu Chen Gang(School of Instrument Science , Engineering,Southeast University,Nanjing 210096,China) |
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| Abstract: | In order to improve the accuracy and reliability of the driving fatigue detection based on a single feature,a new detection algorithm based on multiple features is proposed.Two direct driver's facial features reflecting fatigue and one indirect vehicle behavior feature indicating fatigue are considered.Meanwhile,T-S fuzzy neural network(TSFNN) is adopted to recognize the driving fatigue of drivers.For the structure identification of the TSFNN,subtractive clustering(SC) is used to confirm the fuzzy rules and... |
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| Keywords: | driving fatigue fusion detection particle swarm optimization(PSO) subtractive clustering(SC) |
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