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Coal mine safety production forewarning based on improved BP neural network 被引量:38
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作者 Wang Ying Lu Cuijie Zuo Cuiping 《International Journal of Mining Science and Technology》 SCIE EI CSCD 2015年第2期319-324,共6页
Firstly, the early warning index system of coal mine safety production was given from four aspects as per- sonnel, environment, equipment and management. Then, improvement measures which are additional momentum method... Firstly, the early warning index system of coal mine safety production was given from four aspects as per- sonnel, environment, equipment and management. Then, improvement measures which are additional momentum method, adaptive learning rate, particle swarm optimization algorithm, variable weight method and asynchronous learning factor, are used to optimize BP neural network models. Further, the models are applied to a comparative study on coal mine safety warning instance. Results show that the identification precision of MPSO-BP network model is higher than GBP and PSO-BP model, and MPSO- BP model can not only effectively reduce the possibility of the network falling into a local minimum point, but also has fast convergence and high precision, which will provide the scientific basis for the forewarnin~ management of coal mine safetv production. 展开更多
关键词 Improved PSO algorithm BP neural network Coal mine safety production early warning
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A Real-time Monitoring and Early Warning System for Landslides in Southwest China 被引量:7
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作者 JU Neng-pan HUANG Jian +2 位作者 HUANG Run-qiu HE Chao-yang LI Yan-rong 《Journal of Mountain Science》 SCIE CSCD 2015年第5期1219-1228,共10页
Landslides not only cause property losses,but also kill and injure large numbers of people every year in the mountainous areas. These losses and casualties may be avoided to some extent by early warning systems for la... Landslides not only cause property losses,but also kill and injure large numbers of people every year in the mountainous areas. These losses and casualties may be avoided to some extent by early warning systems for landslides. In this paper, a realtime monitoring network and a computer-aided automatic early warning system(EWS) are presented with details of their design and an example of application in the Longjingwan landslide, Kaiyang County, Guizhou Province. Then, according to principle simple method of landslide prediction, the setting of alarm levels and the design of appropriate counter-measures are presented. A four-level early warning system(Zero, Outlook, Attention and Warning) has been adopted, and the velocity threshold was selected as the main warning threshold for the landslide occurrence, but expert judgment is included in the EWS to avoid false alarms. A case study shows the applicability and reliability for landslide risk management, and recommendations are presented for other similar projects. 展开更多
关键词 LANDSLIDE early warning system (EWS)Wireless sensor network Velocity threshold Longjingwan landslide
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