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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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Exports reflect "safety of products"
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《China Textile》 2007年第8期8-8,共1页
Most of the made-in-China products are absolutely safe, and the steady increase in exports despite the recent widespread criticism reflects their safety standards, a Ministry of Commerce official said Thursday.
关键词 Exports reflect safety of products
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Longwall automation: Delivering enabling technology to achieve safer and more productive underground mining 被引量:30
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作者 Ralston Jonathon C. Reid David C. +1 位作者 Dunn Mark T. Hainsworth David W. 《International Journal of Mining Science and Technology》 SCIE EI CSCD 2015年第6期865-876,共12页
The ongoing need to deliver improved safety, productivity and environmental benefit in coal mining presents an open challenge as well as a powerful incentive to develop new and improved solutions. This paper assesses ... The ongoing need to deliver improved safety, productivity and environmental benefit in coal mining presents an open challenge as well as a powerful incentive to develop new and improved solutions. This paper assesses the critical role that enabling technologies have played in the delivery of remote and automated capability for longwall mining. A brief historical account is given to highlight key technical contributions which have influenced the direction and development of present-day longwall technology. The current state of longwall automation is discussed with particular attention drawn to the technologies that enable automated capability. Outcomes are presented from an independently conducted case study that assessed the impact that CSIRO's LASC longwall automation research has made to the longwall mining industry in Australia. Importantly, this study reveals how uptake of this innova- tive technology has significantly benefitted coal mine productivity, improved working conditions for personnel and enhanced environmental outcomes. These benefits have been widely adopted with CSIRO automation technology being used in 60 per cent of all Australian underground operations. International deployment of the technology is also emerging. The paper concludes with future challenges and opportunities to highfight the ongoing scope for longwall automation research and development. 展开更多
关键词 safety Productivity Environment Mining automation Longwall mining Remote mining
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