【作者】 赵利民； 李雅丹； 王双维； 黄秋晨； 孟颖； 李楠； 张大川； 杨洋； 王春红；

【Author】 ZHAO Li-min~1,LI Ya-dan~(2;3),WANG Shuang-wei~2,HUANG Qiu-chen~2,MENG Ying~1,LI Nan~1, ZHANG Da-chuan~1,YANG Yang~1,WANG Chun-hong~1 (1.Changchun Environmental Monitoring Center,Changchun 130022,China; 2.College of Physics,Northeast Normal University,Changchun 130024,China; 3.College of Physics,Beihua University,Jilin 132013,China)

【机构】 长春市环境监测中心站； 东北师范大学物理学院； 北华大学物理学院；

【摘要】 目前,我国多数城市的交通噪声监测点位选取方法都具有一定局限性,使得监测点位的空间分布不尽合理。为了完成对城市交通噪声污染的正确评价并作出合理的决策和规划,寻找科学的优化噪声监测点位的方法成为实际工作中亟待解决的问题。本文以长春市人民大街交通噪声状况为例,以神经网络为主要技术手段,提出城市"噪声岛"的概念,应用噪声岛"地形"选取交通噪声监测点位,并在此基础上运用灰色系统理论,综合神经网络算法,研究最佳噪声监测点位选取与优化规则。经实验验证,城市"噪声岛"模型在交通噪声监测点位优化中取得了很好的效果。更多还原

【Abstract】 At present,there is a certain limitation of the method selected to choose urban traffic noise monitoring point in China.Accordingly,the problem needs to be addressed in practical issues is how to choose a scientific method to optimize the noise monitoring point,to correctly evaluate the urban traffic noise pollution and also make a reasonable decision and plan. In this paper,the urban"Noise Island"concept is proposed according with the traffic noise situation of ChangChun on renmin street,with neural network as the main technical means.The noise monitoring point is selected by using the"terrain"of"Noise Island".On this basis,the point selection and optimization rules of the best noise monitoring point are studied through out the Grey System Theory and neural network algorithms.Finally the"noise island"model used to optimize the traffic noise monitoring point proved a good effect by verification.更多还原