Analyzing time series data: a comparison of backpropagation and classical winters' methods

被引:0
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作者
James, Barbara E. [1 ]
St. Clair, Daniel C. [1 ]
Rigler, A.K. [1 ]
Doerer, Daniel M. [1 ]
机构
[1] Brown Group, Inc, Clayton, United States
关键词
Adaptive systems - Algorithms - Backpropagation - Computer simulation - Errors - Forecasting - Learning algorithms - Learning systems - Mathematical models - Regression analysis - Statistical methods - Time series analysis;
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摘要
Time series analysis attempts to forecast future events based on observed regularities in the past. The emergence of the field of machine learning in the 1980s, typified by symbolic classifiers and neural networks, provides methods that can adaptively explore a large space of potential models. This paper tests the application of neural networks to time series forecasting by comparing forecasts produced by a feedforward backpropagation neural network with those of Winters' Method, a time series statistic.
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页码:1123 / 1128
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