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Snowfall and rainfall forecasting from weather radar images with artificial neural networks

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5 Author(s)
Ochiai, K. ; Adv. Video Process. Lab., NTT Human Interface Labs., Kanagawa, Japan ; Suzuki, H. ; Shinozawa, K. ; Fujii, M.
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Discusses problems of the weather forecasting technique with artificial neural networks and describes some solutions. The authors show that the computational time for learning with an acceleration learning algorithm can be reduced by about 10 percent. To overcome the problem of overtraining, a pruning method is introduced and the prediction error is decreased by about 20 percent. Using the data obtained over a winter, the neural weather forecasting technique is more effective than the cross correlation method in producing a substantial reduction of prediction error

Published in:

Neural Networks, 1995. Proceedings., IEEE International Conference on  (Volume:2 )

Date of Conference:

Nov/Dec 1995

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