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Classification of frozen soil blastability by using perceptron neural network 被引量:1

Classification of frozen soil blastability by using perceptron neural network
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摘要 Influence factors of frozen soil blastability are analyzed which mainly conclude the strain energy coefficient, tensile strength, compressive strength, longitudinal wave velocity and transverse wave velocity. According to the principle of perceptron neural network, at first the index factors are standardized by the aid of the efficient function theory, then the blastability of frozen sand at -7, -12 and -17 ℃ are classified three categories. Through adjusting the weight value and threshold value, we can obtain that the clay blastability at -7 ℃ is close to the sand blastability at -12 ℃, they belong to the second category, the clay blastability at -12 ℃ is close to the sand blastability at -17 ℃, thus they are divided into the third category. Influence factors of frozen soil blastability are analyzed which mainly conclude the strain energy coefficient, tensile strength, compressive strength, longitudinal wave velocity and transverse wave velocity. According to the principle of perceptron neural network, at first the index factors are standardized by the aid of the efficient function theory, then the blastability of frozen sand at -7, -12 and -17 ℃ are classified three categories. Through adjusting the weight value and threshold value, we can obtain that the clay blastability at -7 ℃ is close to the sand blastability at -12 ℃, they belong to the second category, the clay blastability at -12 ℃ is close to the sand blastability at -17 ℃, thus they are divided into the third category.
出处 《Journal of Coal Science & Engineering(China)》 2002年第1期54-58,共5页 煤炭学报(英文版)
基金 SupportedbyOutstandingYouthFoundationforScientificandTechnologicalResearchofAnhuiProvince ( 2 0 0 1-2 8)
关键词 frozen soil BLASTABILITY neural network PERCEPTRON CLASSIFICATION 冻土 可爆性 神经网络 感知器 分类
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  • 1崔广心,相似理论与模型试验,1990年
  • 2潘井澜,隧道译丛,1978年,5期,1页

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