Basel Accords and to their internal computations of economic capital. In this paper, support vector regression (SVR … improved versions of support vector regression techniques outperform other methods significantly. Second, at a segmented level …, by bond seniority, least square support vector regression demonstrates significantly better predictive abilities compared …

assumptions about volatility underlying process. Recently, a supervised learning machine called support vector regression …

(support vector regression) and PSO (particle swarm optimization). In order to solve the noise and stationarity problems in the …

in the raw wind speed data to achieve accurate forecasting. In this paper, Support Vector Regression (SVR), a learning …

Vector Regression (SVR) methodology that originates from machine learning. We test the forecasting ability of the proposed … methodology that combines the Ensemble Empirical Mode Decomposition (EEMD) from the field of signal processing with the Support …

This paper presents a novel approach, named the SVR (support vector regression) based SVRLP (support vector regression … local predictor) with FNF-SVRLP (false neighbours filtered-support vector regression local predictor), to predict short …

used extensively for modeling river flow data. The use of machine learning techniques such as support-vector regression and …-layer feed forward network trained with a back-propagation algorithm and support vector regression with epsilon intensive …

techniques, namely, neuro-fuzzy logic and support vector regression (SVR) techniques for the assessment of cutting tools. In this …