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- W1966774294 abstract "AbstractIn mine valuation commodity price forecasts are required to assess the economic viability of a project. The forecast must cover a relevant period to capture the trend and volatility in prices within a mining business cycle. Mineral commodity prices are volatile, which means that the results of evaluation tools that do not treat the stochasticity of metal prices rigorously may be misleading.A model has been set up in which the gold price is modelled by a three-step procedure: a multivariate, normally distributed random variable generator (MNDRVG), the method of multilayer feed-forward neural networks (MFNN) and multiple regression analysis. The first step uses MNDRVG to generate the input data. In the second step the data are fed into an orthogonal projection model to estimate the parameters of a linear regression. In the third step the estimated regression is used to forecast the gold price. Because not all the input data are known at the time of the forecast, MFNN is used to generate the unknown ..." @default.
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- W1966774294 date "2000-04-01" @default.
- W1966774294 modified "2023-09-26" @default.
- W1966774294 title "Stochastic model of mineral prices incorporating neural network and regression analysis" @default.
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- W1966774294 doi "https://doi.org/10.1179/mnt.2000.109.1.49" @default.
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