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- W2299291283 abstract "The characteristics of the response of the rock mass around an opening to an adjacent or nearby excavation are important in designing optimum mining sequences, as well as an adequate mining method. Also, it is possible to estimate the elastic deformational behaviour immediately after creating an excavation by investigating the response of the rock mass to the sudden stress change due to this adjacent excavation. The effect of an adjacent excavation on an existing excavation can be clearly shown by various types of displacement plots. When an excavation is created near the measuring location, the deformation of the location increases rapidly as the adjacent excavation is created. The amount of deformation increase caused by adjacent mining seems to be dependent on several factors such as the mining method, the measuring location, the distance between the measuring location and the newly excavated opening, and opening geometry. The duration of influence can also be affected by these factors. Thus, the prediction of the influence of an adjacent excavation on the deformation and deformation rate change, is especially difficult. The application of neural networks can provide a useful tool for predicting the influence of an adjacent excavation on existing mine workings, and for deriving relationships between deformation change due to the adjacent excavation and each parameter. This is possible because of the following reasons: firstly, neural networks can use qualitative information as input or output. Regression equations require only quantitative information for input, but in neural networks, qualitative parameters such as rock type, location of measurement, or mining type can also be incorporated; secondly, there is no limit to the number of inputs or outputs; thirdly, neural networks can be used to solve complicated non-linear problems, and complex relationships between input and output; and finally, it is not necessary to know the general relationship between input and output variables before carrying out the data analysis. Neural networks are capable of modelling input-output functional relations, even when mathematically explicit formulas are unavailable (Szewczyk and Hajela, 1994)." @default.
- W2299291283 created "2016-06-24" @default.
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- W2299291283 date "1998-01-01" @default.
- W2299291283 modified "2023-09-23" @default.
- W2299291283 title "Investigation of the Influence of an Excavation on Adjacent Excavations, Using Neural Networks" @default.
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