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- W1956295622 abstract "This paper presents a grid computing approach to parallel-process a neural network time-series model for forecasting electricity market prices. A grid computing environment introduced in a university computing laboratory provides access to otherwise underused computing resources. The grid computing of the neural network model not only processes several times faster than a single iterative process, but also provides chances of improving forecasting accuracy. Results of numerical tests using real market data on twenty grid-connected PCs are reported." @default.
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- W1956295622 date "2007-01-01" @default.
- W1956295622 modified "2023-09-23" @default.
- W1956295622 title "ELECTRICITY MARKET PRICE FORECASTING BY GRID COMPUTING OPTIMIZING ARTIFICIAL NEURAL NETWORKS" @default.
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