Accurate load forecasting is an important issue for the reliable and efficient operation of the power system. This paper presents a hybrid algorithm which combines SVR (support vector regression), RBFNN (radial basis function neural network), and DEKF (dual extended Kalamn filter) to construct a...

В статье осуществлены анализ и оценка характеристик финансовых состояний предприятий машиностроения. Предложен алгоритм выбора показателей для оценки...

Forecasting returns for the Artificial Intelligence and Robotics Index is of great significance for financial market stability, and the development of the artificial intelligence industry. To provide investors with a more reliable reference in terms of artificial intelligence index investment,...

This paper proposes a hybrid STLF (short-term load forecasting) framework with a new input selection method. BNN (Bayesian neural network) is used to forecast the load. A combination of the correlation analysis and ℓ2-norm selects the appropriate inputs to the individual BNNs. The correlation...