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Volume 12 Issue 2

Apr.  1995

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Article >  ADVANCES IN ATMOSPHERIC SCIENCES  > 1995 >  12(2): 225-232

Monthly Mean Temperature Prediction Based on a Multi-level Mapping Model of Neural Network BP Type

  • 1.

    Nanjing Institute of Meteorology, Nanjing 210044,Nanjing Institute of Meteorology, Nanjing 210044,Nanjing Institute of Meteorology, Nanjing 210044


doi: 10.1007/BF02656835

  • 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 D0 = 2.8, leading to a three-level model of this type with i × j = 3 × 2, k = 1, and the 1980 monthly mean temperture prediction on a long-term basis were pre-pared by steadily modifying the weighting coefficient, making for the correlation coefficient of 97% with the measurements. Furthermore, the weighting parameter was modified for each month of 1980 by means of observations, therefore constructing 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 correlation of 98% and the month-to month forecasts of 99.4%.
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    • Manuscript History

    Manuscript received: 10 April 1995
    Manuscript revised: 10 April 1995
    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

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    Monthly Mean Temperature Prediction Based on a Multi-level Mapping Model of Neural Network BP Type

    • 1. Nanjing Institute of Meteorology, Nanjing 210044,Nanjing Institute of Meteorology, Nanjing 210044,Nanjing Institute of Meteorology, Nanjing 210044
    • Manuscript received: 1995-04-10
    • Manuscript revised: 1995-04-10

    Abstract: 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 D0 = 2.8, leading to a three-level model of this type with i × j = 3 × 2, k = 1, and the 1980 monthly mean temperture prediction on a long-term basis were pre-pared by steadily modifying the weighting coefficient, making for the correlation coefficient of 97% with the measurements. Furthermore, the weighting parameter was modified for each month of 1980 by means of observations, therefore constructing 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 correlation of 98% and the month-to month forecasts of 99.4%.

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