Abstract
Neural network technology is experiencing rapid growth and is receiving considerable attention from almost every field of science and engineering. The attraction is due to the successful application of neural network techniques to several real world problems. Neural networks have not yet found widespread application in weather forecasting. The reason for this has been the difficulty in obtaining suitable weather forecasting data sets. In this paper we describe our experience in applying neural network techniques for acquiring the necessary knowledge to predict the weather conditions of Melbourne City and its suburbs in Australia during a 24 hour period beginning at 9 am local time. The accuracy of forecasts produced by a given forecasting procedure typically varies with factors such as geographical location, season, categories of weather, quality of input data, lead time and validity time. Two types of weather data sets assembled from the archives of the Australian Commonwealth Bureau of Meteorology are used for training the neural network. The results of the experiments are competitive and are discussed.
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Chung, C.Y.C., Kumar, V.R. Knowledge acquisition using a neural network for a weather forecasting knowledge-based system. Neural Comput & Applic 1, 215–223 (1993). https://doi.org/10.1007/BF01414951
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DOI: https://doi.org/10.1007/BF01414951