Short-term electricity price forecasting using wavelet and SVM techniques

In deregulated electricity market, modeling and forecasting the spot price present a number of challenges. By applying wavelet and support vector machine techniques, a new time series model for short term electricity price forecasting has been developed in this paper. The model employs both historical price and other important information, such as load capacity and weather (temperature), to forecast the price of one or more time steps ahead. The developed model has been evaluated with the actual data from Australian National Electricity Market. The simulation results demonstrated that the forecast model is capable of forecasting the electricity price with a reasonable forecasting accuracy.

Concreteness effects in different tasks: implications for models of short-term memory

This study investigates concreteness effects in tasks requiring short-term retention. Concreteness effects were assessed in serial recall, matching span, order reconstruction, and free recall. Each task was carried out both in a control condition and under articulatory suppression. Our results show no dissociation between tasks that do and do not require spoken output. This argues against the redintegration hypothesis according to which lexical-semantic effects in short-term memory arise only at the point of production. In contrast, concreteness effects were modulated by task demands that stressed retention of item versus order information. Concreteness effects were stronger in free recall than in serial recall. Suppression, which weakens phonological representations, enhanced the concreteness effect with item scoring. In a matching task, positive effects of concreteness occurred with open sets but not with closed sets of words. Finally, concreteness effects reversed when the task asked only for recall of word positions (as in the matching task), when phonological representations were weak (because of suppression), and when lexical semantic representations overactivated (because of closed sets). We interpret these results as consistent with a model where phonological representations are crucial for the retention of order, while lexical-semantic representations support maintenance of item identity in both input and output buffers.