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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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