Grade Interpolation Using Radial Basis Function Networks
نویسنده
چکیده
This paper analyses the application of Radial Basis Function (RBF) networks in grade interpolation. These networks are a very unique member of the family of Artificial Neural Networks. RBF networks have such theoretical properties that establish them as a potential alternative to existing grade interpolation techniques. Their suitability to the problem of grade interpolation will be demonstrated in this paper both theoretically and through a number of case studies from real and simulated mineral deposits.
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