【作者】 曾君； 郭华芳； 胡跃明；

【Author】 Jun Zeng , Huafang Guo, Yueming Hu College of Automation Science and Engineering,South China University of Technology,Guangzhou,510640 Automation Engineering R&M Center, Guangdong Academy of sciences, Guangzhou, 510070

【机构】 华南理工大学自动化科学与工程学院；

【摘要】 汽车尾气是城市主要污染源之一。本文在简要介绍汽车尾气遥感监测的基础上,以广州市2004年遥感监测数据作为基础,主要研究出租车污染情况,利用BP神经网络对汽车尾气排放超标进行判断,以探讨神经网络技术在尾气污染预测中的应用。网络仿真结果表明,利用神经网络进行预测的准确率达到93％,优于传统方法建模的准确率。更多还原

【Abstract】 Vehicle emission is a major source of air pollution in urban cities. After the introduction of vehicle emissions remote sensing technology, the neural network model for high emitter prediction is made based on the 2004 remote sensing data of Guangzhou. The results show that satisfactory prediction was obtained by reasonable selection of original data for input layer element and algorithm. And the correct rate and the ability of generalization are superior to the traditional model in prediction.更多还原