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This paper contains a forecasting exercise on 30 time series, ranging on several fields, from economy to ecology. The statistical approach to artificial neural networks modelling developed by the author is compared to linear modelling and to other three well-known neural network modelling...
Persistent link: https://www.econbiz.de/10010281250
This paper contains a forecasting exercise on 30 time series, ranging on several fields, from economy to ecology. The statistical approach to artificial neural networks modelling developed by the author is compared to linear modelling and to other three well-known neural network modelling...
Persistent link: https://www.econbiz.de/10005190861
Persistent link: https://www.econbiz.de/10001639532
Persistent link: https://www.econbiz.de/10001639534
This paper contains a forecasting exercise on 30 time series, ranging on several fields, from economy to ecology. The statistical approach to artificial neural networks modelling developed by the author is compared to linear modelling and to other three well-known neural network modelling...
Persistent link: https://www.econbiz.de/10001645582
Persistent link: https://www.econbiz.de/10001695858
This paper is concerned with modelling time series by single hidden-layer feedforward neural network models. A coherent modelling strategy based on statistical inference is presented. Variable selection is carried out using existing techniques. The problem of selecting the number of hidden units...
Persistent link: https://www.econbiz.de/10001693108
Persistent link: https://www.econbiz.de/10003268447