Abstract
A neuroid BP-type three-layer mapping model is used for monthly rainfall forecasting in terms of 1946–1985 Nanjing monthly precipitation records as basic sequences and the model has the formi × j = 8 × 3,K = 1; by steadily modifying the weighing coefficient, long-range monthly forecasts for January to December, 1986 are constructed and 1986 month-to-month predictions are made based on, say, the January measurement for February rainfall and so on, with mean absolute error reaching 6,07 and 5,73 mm, respectively. Also, with a different monthly initial value for June through September, 1994, neuroid forecasting is done,indicating the same result of the drought in Nanjing during the summer, an outcome that is in sharp agreement with the observation.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Jiao Licheng (1990),Neuroid Theory, Xi’an Electronic Sci./Tech. Univ. Press, pp. 34–36 (in Chinese).
Yan Shaojin and Peng Yongqing (1993),Chaos Theory and Atmospheric Sciences, China Meteorological Press, pp. 111–116 (in Chinese).
Yan Shaojin, Peng Yongqing and Guo Guang (1995), Monthly Mean Temperature Prediction Based on a Multi-Level Mapping Model of Neural Network BP Type,Advances in Atmospheric Sciences, 12: 225–232.
Author information
Authors and Affiliations
Additional information
This study is supported by the National Natural Science Foundation of China.
Rights and permissions
About this article
Cite this article
Shaojin, Y., Yongqing, P. & Guang, G. Neuroid BP-type model applied to the study of monthly rainfall forecasting. Adv. Atmos. Sci. 12, 335–342 (1995). https://doi.org/10.1007/BF02656982
Received:
Revised:
Issue Date:
DOI: https://doi.org/10.1007/BF02656982