Abstract Aiming at the time-varying and fluctuating characteristics of photovoltaic power output, a GA-Elman model is proposed for short-term prediction active power. This can use historical value daily meteorological information to directly forecast power, which convenient dispatching department supply bureau obtain output data in advance enhance reliability supply. Firstly, input variables El...

The greenhouse effect and its extension affecting is one of the key issues to governments and academics currently. Study shows, CO2 produced from burning fossil fuels are liable 2/3 of the above-mentioned problems. CO2 emissions in China are mainly concentrated in the power plants. In this paper, Gray Markov method is used for long-term load forecasting, combined with the prediction of power ge...

Branch prediction is one of the ancient performance improving techniques which still finds relevance into modern architectures. While the simple prediction techniques provide fast lookup and power efficiency they suffer from high misprediction rate. On the other hand, complex branch predictions – either neural based or variants of two-level branch prediction – provide better prediction accuracy...

Photovoltaic energy production is an important factor for increasing the electricity supply. The ability to predict electric power (EPP) of a photovoltaic (PV) farm supports from management process grid trade in market and much more. Also, by predicting PV (PVP), it possible monitor lifetime solar cells that form backbone any system. As critical result, sudden failures plant can be avoided. Usi...

Way-prediction (WP) caches have advantages of reducing power consumption and latency for highly associative data caches and thus are favorable for embedded systems. In this paper, we propose an enhanced way-prediction cache, dual-access way-prediction (DAWP) cache, to cope with the weakness of the WP cache. The prediction logic designed for the DAWP cache contains a scaled index table, a global...