检索规则说明:AND代表“并且”;OR代表“或者”;NOT代表“不包含”;(注意必须大写,运算符两边需空一格)
检 索 范 例 :范例一: (K=图书馆学 OR K=情报学) AND A=范并思 范例二:J=计算机应用与软件 AND (U=C++ OR U=Basic) NOT M=Visual
作 者:李鹏[1,2,3] 嵇佳丽 丁倩雯 LI Peng;JI Jiali;DING Qianwen(Jiangsu Key Laboratory of Meteorological Observation and Information Processing,Nanjing University of Information Science and Technology,Nanjing 210044;Jiangsu Collaborative Innovation Center on Atmospheric Environment and Equipment Technology,`Nanjing University of Information Science and Technology,Nanjing 210044;Binjiang College of Nanjing University of Information Science and Technology,Wuxi 214105)
机构地区:[1]南京信息工程大学,江苏省气象探测与信息处理重点实验室,南京210044 [2]南京信息工程大学,江苏省大气环境与装备技术协同创新中心,南京210044 [3]南京信息工程大学,滨江学院,无锡214105
出 处:《气象》2021年第7期854-861,共8页Meteorological Monthly
基 金:江苏省重点研发计划社会发展项目(BE2015692);无锡市社会发展科技示范工程项目(N20191008);南京信息工程大学无锡校区研究生创新实践项目(WXCX201913)共同资助。
摘 要:针对冰雹监测难和冰雹灾情不易估计的问题,结合声信号的时域、频域特点,采用时域、频域和小波域相结合的特征提取方法,将熵值法与广义回归神经网络(GRNN)相结合,提出一种基于熵值法特征筛选的GRNN降雹识别方法。对采集的降雹和降雨声信号提取时域特征、频域特征和小波包能量谱特征,采用熵值法确定各特征的权重大小,剔除权重较小的特征项并进行特征融合组成新的特征子集,将特征子集输入GRNN进行预测识别。试验结果表明,该方法能够有效识别冰雹,且特征筛选后的识别率高达97.8276%,相较未进行特征筛选的特征集,识别率提高了近10%。In view of the difficulty in hail monitoring and hail disaster estimation,combined with the characteristics of acoustic signal in time and frequency domain,this paper proposes a generalized regression neural network(GRNN)hail detection method based on entropy method by combining the entropy method with the GRNN.The time domain feature,frequency domain feature and wavelet packet energy spectrum feature are extracted from the collected hail and rain sound signals.The entropy method is used to determine the weight of each feature.The feature items with smaller weight are eliminated and fused to form a new feature subset.The feature subset is input into GRNN for prediction and recognition.The experimental results show that the method can effectively identify hail,and the recognition rate after feature screening is as high as 97.8276%,which is nearly 10%higher than that of the feature set without feature screening.
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在链接到云南高校图书馆文献保障联盟下载...
云南高校图书馆联盟文献共享服务平台 版权所有©
您的IP:3.16.56.30