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Forecasting time series accurately is critical to ensure the safety and reliability of complex system. So, time series prediction has been a popular subject. Normally, the information used in time series prediction is always mined from multi-variable time series and small simple data. Thus, based on grey prediction theory, an adaptive prediction model with multi-variable small simple time series data...
Under deregulated environment, accurate electricity price forecasting is a crucial issue concerned by all participants. Experience shows that single forecasting model is very difficult to improve the forecasting accuracy due to the complicated factors affecting electricity prices. A particle swarm optimization (PSO) based GM(1,2) method on day-ahead electricity price forecasting with predicted error...
Fuzzy time series (FTS) has become an effective method for forecasting some typical time series-enrollments, stock price and daily price of foreign exchange-due to its salient capacities for dealing with uncertainty, vagueness in historical observations. However, how to partition the universe of discourse and how to construct fuzzy logic relationships are two unsolved problems which may affect the...
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