Time Series Prediction with Artiicial Neural Networks
نویسنده
چکیده
This research project investigates the ability of artiicial neural networks (ANNs) to predict time series. Speciically, this project examined two applications: predicting electrical power demand and earthquake tremors in Los Angeles. The ANNs modeling power demand not only predicted the next day's peak power demand, but also generated a 24-hour proole of the demand for the next day. These ANNs successfully outperformed the predictive ability of a system used by the Los Angeles Department of Water and Power (LADWP). In addiiton, it also performed on par with industry-standard ANNs. The second application earthquake prediction was not able to predict earthquake tremors. Due to the voluminous amounts of data, better results may only be obtained through researching methods of on-line feature extraction and data preprocessing.
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