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Forecasting Energy Demand Using Conditional Random Field and Convolution Neural Network
Elektronika ir Elektrotechnika
Electric load forecasting has been identified as an effective strategy to increase output and revenues in electrical manufacturing and distribution organizations. Several strategies for forecasting power consumption have been suggested; however, they all fail to account for small variations in power demand throughout the prediction. Therefore, the aim of this study was to develop a CRF-based power consumption prediction technique (CRF-PCP) to meet the difficulty of estimating energy consumptiondoi:10.5755/j02.eie.30740 fatcat:lzsbsjgmijasbeu5uodt626ekq