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首页> 外文期刊>Mining & Minerals >Researchers at Dalian University of Technology Release New Data on Mining and Metallurgy (Waveform Recognition and Process Interpretation of Microseismic Monitoring Based On an Improved Lenet5 Convolutional Neural Network)
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Researchers at Dalian University of Technology Release New Data on Mining and Metallurgy (Waveform Recognition and Process Interpretation of Microseismic Monitoring Based On an Improved Lenet5 Convolutional Neural Network)

机译:大连理工大学科研人员发布矿山冶金新数据(基于改进Lenet5卷积神经网络的微震监测波形识别与过程解释)

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摘要

2023 JUN 23 (VerticalNews) – By a News Reporter-Staff News Editor at Mining & Minerals – Investigators discuss new findings in Technology - Mining and Metallurgy. According to news reporting from Dalian, People’s Republic of China, by VerticalNews journalists, research stated, “The development of high-precision and interpretable automatic waveform classification algorithms with strong adaptability is becoming increasingly significant under the background of the big data era of microseismicity. Considering the deficiency of the existing network in waveform recognition and classification, an improved model which is suitable for microseismic (MS) monitoring waveform recognition was proposed in this study based on the LeNet framework.”
机译:2023年6月23日(VerticalNews)——由一个消息记者在采矿和矿物-新闻编辑调查人员在技术讨论新发现采矿和冶金。报告从大连人民共和国VerticalNews记者,中国研究说:“高精度和的发展可翻译的波形自动分类算法具有较强的适应性日益显著的背景下大数据时代的微震动。现有网络的缺陷波形识别和分类改进的模型适用于微震的(MS)监测波形识别提出了在这项研究中基于LeNet框架。”

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    《Mining & Minerals》 |2023年第23期|85-86|共2页
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  • 正文语种 英语
  • 中图分类 矿业工程;
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