A neuroid BP-type three-layer mapping model is used for monthly rainfall forecasting in terms of 1946-1985Naming monthly precipitation records as basic sequences and the model has the form i×j=8×3, K=1; by s...A neuroid BP-type three-layer mapping model is used for monthly rainfall forecasting in terms of 1946-1985Naming monthly precipitation records as basic sequences and the model has the form i×j=8×3, K=1; by steadilymodifying the weighing coefficient, long-range monthly forecasts for January to December, 1986 are constructed and1986 month-to-month predictions are made based on, say, the January measurement for February rainfall and soon, with mean absolute error reaching 6,07 and 5,73 mm, respectively. Also, with a different monthly initial value forJune through September, 1994, neuroid forecasting is done,indicating the same result of the drought in Naming during the summer, an outcome that is in sharp agreement with the observation.展开更多
In terms of 34-year monthly mean temperature series in 1946-1979,the multi-level maPPing model of neural netWork BP type was applied to calculate the system's fractual dimension Do=2'8,leading tO a three-level...In terms of 34-year monthly mean temperature series in 1946-1979,the multi-level maPPing model of neural netWork BP type was applied to calculate the system's fractual dimension Do=2'8,leading tO a three-level model of this type with ixj=3x2,k=l,and the 1980 monthly mean temperture predichon on a long-t6rm basis were prepared by steadily modifying the weighting coefficient,making for the correlation coefficient of 97% with the measurements.Furthermore,the weighhng parameter was modified for each month of 1980 by means of observations,therefore constrcuhng monthly mean temperature forecasts from January to December of the year,reaching the correlation of 99.9% with the measurements.Likewise,the resulting 1981 monthly predictions on a long-range basis with 1946-1980 corresponding records yielded the correlahon of 98% and the month-tO month forecasts of 99.4%.展开更多
文摘A neuroid BP-type three-layer mapping model is used for monthly rainfall forecasting in terms of 1946-1985Naming monthly precipitation records as basic sequences and the model has the form i×j=8×3, K=1; by steadilymodifying the weighing coefficient, long-range monthly forecasts for January to December, 1986 are constructed and1986 month-to-month predictions are made based on, say, the January measurement for February rainfall and soon, with mean absolute error reaching 6,07 and 5,73 mm, respectively. Also, with a different monthly initial value forJune through September, 1994, neuroid forecasting is done,indicating the same result of the drought in Naming during the summer, an outcome that is in sharp agreement with the observation.
文摘In terms of 34-year monthly mean temperature series in 1946-1979,the multi-level maPPing model of neural netWork BP type was applied to calculate the system's fractual dimension Do=2'8,leading tO a three-level model of this type with ixj=3x2,k=l,and the 1980 monthly mean temperture predichon on a long-t6rm basis were prepared by steadily modifying the weighting coefficient,making for the correlation coefficient of 97% with the measurements.Furthermore,the weighhng parameter was modified for each month of 1980 by means of observations,therefore constrcuhng monthly mean temperature forecasts from January to December of the year,reaching the correlation of 99.9% with the measurements.Likewise,the resulting 1981 monthly predictions on a long-range basis with 1946-1980 corresponding records yielded the correlahon of 98% and the month-tO month forecasts of 99.4%.
