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4.1 Subject of the study
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4.2 Scope of the study
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Hypothesis 1: In the case of steep curb, the Asadi model with coefficients f, g,
p, q determined from the field observation data allows the prediction of the ground subsidence in exploited areas with the same conditions
Hypothesis 2: The artificial neural network with one hidden layer in which a supervised training method and a backpropagation algorithm are utilized can accurately forecast the subsidence overtime when the number of observation cycles
is more than eight.
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a Scientific significance
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b Practical significance
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Figure 1.2 Zones of influence
1.1.3 Ground movement angles
1.1.4 Movement and deformation parameters
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2.1.3 Excavation techniques in Quang Ninh underground coal mines
2.1.4 Characteristics of working face
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