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区域噪声监测点位的噪声岛地形布点法应用初探
引用本文:赵利民,李雅丹,王铮,王双维.区域噪声监测点位的噪声岛地形布点法应用初探[J].噪声与振动控制,2011,31(2):142-146.
作者姓名:赵利民  李雅丹  王铮  王双维
作者单位:( 1. 长春市环境监测中心站, 长春 130022 ; 2. 东北师范大学 物理学院, 长春 130024;3. 北华大学 物理学院, 吉林 132013; 4. 吉林省环境监测中心站, 长春 130021 )
摘    要:环境噪声污染日趋严重的影响人们的正常生活。应用科学的优化噪声监测点位的方法,可对区域环境噪声污染进行正确评价,对政府的决策及规划管理具有重要意义。目前,多数城市的区域环境噪声监测点位优化方法,都具有一定局限性。以吉林省长春市某区域为例,采用集成神经网络为主要技术手段,首次应用“噪声岛”地形法对区域环境噪声监测点位进行优化选取,并在此基础上对最佳噪声监测点位选取与优化规则进行初步探究。

关 键 词:声学  区域噪声  监测点位优化  神经网络集成  噪声岛  

Preliminary Study on "Noise Island" Topographic Distribution Method Applied in Urban Region Noise Monitoring Points Optimization
ZHAO Li-min,LI Ya-dan,WANG Zheng,WANG Shuang-wei.Preliminary Study on "Noise Island" Topographic Distribution Method Applied in Urban Region Noise Monitoring Points Optimization[J].Noise and Vibration Control,2011,31(2):142-146.
Authors:ZHAO Li-min  LI Ya-dan  WANG Zheng  WANG Shuang-wei
Affiliation:( 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;4. Jilin Province Environmental Monitoring Center, Changchun 130011, China )
Abstract:Environmental noise pollution is influencing our daily life seriously.The regional noise pollution can be evaluated by using noise monitoring point optimization method.It has an important significance for planning and management of the environment.At present,there are some limitations for application of the environmental noise monitoring point optimization methods to urban regions in China.In this paper,the urban "Noise Island" concept is proposed.The environmental noise monitoring point optimization of an area in Changchun is carried out as an example applying the "Noise Island" topographic distribution method,with integrated neural network as the main technical means.The noise monitoring point is selected by using the "terrain" of the "Noise Island" for the first time.On this basis,the point selection and optimization rules of the best noise monitoring point distribution are found.
Keywords:acoustics  region noise  noise monitoring point optimization  neural network ensemble  noise island
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