A Method of Forecasting Thunderstorms and Gale Weather Based on Multisource Convolution Neural Network

The local thunderstorms and gale weather occurring frequently has brought huge losses to the agriculture and transportation industries. This paper presents a method of forecasting the local thunderstorms and gale weather, in which a multisource convolution neural network is constructed to extract th...

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Main Authors: Yanping Jiang, Jinliang Yao, Zheng Qian
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/8781906/
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author Yanping Jiang
Jinliang Yao
Zheng Qian
author_facet Yanping Jiang
Jinliang Yao
Zheng Qian
author_sort Yanping Jiang
collection DOAJ
description The local thunderstorms and gale weather occurring frequently has brought huge losses to the agriculture and transportation industries. This paper presents a method of forecasting the local thunderstorms and gale weather, in which a multisource convolution neural network is constructed to extract the features of weather-related data with multiple types from Doppler radar. To improve the discriminative power of features, Center-Loss and Softmax were jointly used as loss function in the training, and then the features obtained are combined with SVM for classification. Furthermore, a comparative experiment of multisource convolution neural network based on CNN-4, ResNet30, ResNet50, and VGG16 is designed, in which the ResNet30 achieves the highest accuracy. The experimental results show that the multisource convolution neural network avoids the limitation of using one type of data and improves the accuracy of forecasting local thunderstorms and gale.
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spelling doaj.art-576fb848042f4dd1ac9cd72303c7b4802022-12-21T23:22:52ZengIEEEIEEE Access2169-35362019-01-01710769510769810.1109/ACCESS.2019.29320278781906A Method of Forecasting Thunderstorms and Gale Weather Based on Multisource Convolution Neural NetworkYanping Jiang0https://orcid.org/0000-0001-7233-1157Jinliang Yao1Zheng Qian2School of Computer Science, Hangzhou Dianzi University, Xiasha Higher Education Zone, Hangzhou, ChinaSchool of Computer Science, Hangzhou Dianzi University, Xiasha Higher Education Zone, Hangzhou, ChinaNingbo Meteorological Service Center, Ningbo, ChinaThe local thunderstorms and gale weather occurring frequently has brought huge losses to the agriculture and transportation industries. This paper presents a method of forecasting the local thunderstorms and gale weather, in which a multisource convolution neural network is constructed to extract the features of weather-related data with multiple types from Doppler radar. To improve the discriminative power of features, Center-Loss and Softmax were jointly used as loss function in the training, and then the features obtained are combined with SVM for classification. Furthermore, a comparative experiment of multisource convolution neural network based on CNN-4, ResNet30, ResNet50, and VGG16 is designed, in which the ResNet30 achieves the highest accuracy. The experimental results show that the multisource convolution neural network avoids the limitation of using one type of data and improves the accuracy of forecasting local thunderstorms and gale.https://ieeexplore.ieee.org/document/8781906/Feature extractionDoppler radarforecastingcenter_loss
spellingShingle Yanping Jiang
Jinliang Yao
Zheng Qian
A Method of Forecasting Thunderstorms and Gale Weather Based on Multisource Convolution Neural Network
IEEE Access
Feature extraction
Doppler radar
forecasting
center_loss
title A Method of Forecasting Thunderstorms and Gale Weather Based on Multisource Convolution Neural Network
title_full A Method of Forecasting Thunderstorms and Gale Weather Based on Multisource Convolution Neural Network
title_fullStr A Method of Forecasting Thunderstorms and Gale Weather Based on Multisource Convolution Neural Network
title_full_unstemmed A Method of Forecasting Thunderstorms and Gale Weather Based on Multisource Convolution Neural Network
title_short A Method of Forecasting Thunderstorms and Gale Weather Based on Multisource Convolution Neural Network
title_sort method of forecasting thunderstorms and gale weather based on multisource convolution neural network
topic Feature extraction
Doppler radar
forecasting
center_loss
url https://ieeexplore.ieee.org/document/8781906/
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