In this paper, the SCE-UA algorithm, which is an effective and efficient method to optimize model parameters and widely applied to optimize the parameters of ...
In this paper, the regression SVM is used to forecast daily load and the SCE-UA algorithm is used to select the parameters of SVM automatically. The method.
The proposed SCE-UA SVM model provides a promising alternative for forecasting electricity load and outperforms the BPNN model, which has obtained wide ...
Support vector machine (SVM) is a novel type of learning machine, which has been successfully applied to short-term electricity load forecasting.
Analysis of the experimental results proved that SVM could achieve greater accuracy and faster speed than the BP neural network. A novel method based on SVM ...
Short-term hourly load forecasting using time-series model- ing with peak load estimation capability. IEEE Transactions on Power. Systems, 16(3):498–505 ...
Missing: SCE- UA
And the SCE-UA algorithm is only performed to identify the SVM parameters through some exponential transformation. SUPPORT VECTOR MACHINES FOR REGRESSION (SVR).
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... Short-term load fore- casting using support vector machine with SCE-UA algorithm. In: Third International Conference on Natural Computation. (ICNC 2007) ...
In this paper, the support vector machine (SVM) is presented as a promising method for hydrological prediction. Over-fitting and local optimal solution are ...
Abstract—This paper presents a generic strategy for short-term load forecasting (STLF) based on the support vector regression machines (SVR).