This paper proposes a novel transmission line fault location scheme, combining stationary wavelet transform (SWT), determinant function feature (DFF), support vector machine (SVM) and support vector regression (SVR). Various types of faults at different locations, fault impedance and fault inception angles on a 400 kV, 361.297 km transmission line are investigated. The system only utilizes sing...

Digital color image watermarking algorithm based on scale-invariant feature transform(SIFT) and support vector regression(SVR) is proposed in this paper. The input feature vectors are selected in the wavelet domain and then the train model is obtained by applying the support vector regression theory. The watermark information can be embedded or extracted by utilizing the above trained SVR model...

In this paper, a novel strategy for forecasting outdoor scenes is introduced. It is an approach combining the support vector regression in neural network computation, the discrete cosine transform. In 1995, Vapnik first introduced a neural-network algorithm called support vector machine (SVM). During recent years, due to SVM‘s high generalization performance and its attractive modeling features...

A new smoothing strategy for solving 2-support vector regression (2-SVR), tolerating a small error in fitting a given dataset linearly or nonlinearly, is proposed in this paper. Conventionally, 2-SVR is formulated as a constrained minimization problem, namely a convex quadratic programming problem. We apply the smoothing techniques that have been used for solving the support vector machine for ...

Proteins in living organisms express various important functions by interacting with other proteins and molecules. Therefore, many efforts have been made to investigate and predict protein-protein interactions (PPIs). Analysis of strengths of PPIs is also important because such strengths are involved in functionality of proteins. In this paper, we propose several feature space mappings from pro...

The paper focuses on the task of predicting future values of stock market index. Two indices namely CNX Nifty and S&P Bombay Stock Exchange (BSE) Sensex from Indian stock markets are selected for experimental evaluation. Experiments are based on 10 years of historical data of these two indices. The predictions are made for 1–10, 15 and 30 days in advance. The paper proposes two stage fusion app...

Slope stability is one of the most complex and essential issues for civil and geotechnical engineers, mainly due to life and high economical losses resulting from these failures. In this paper, a new approach is presented for estimating the Safety Factor (SF) for circular failure slope using hybrid support vector regression (SVR) and Ant Colony Optimization (ACO). The ACO is combined with the S...

Displacements induced by earthquake can be very large and result in severe damage to earth and earth supported structures including embankment dams, road embankments, excavations and retaining walls. It is important, therefore, to be able to predict such displacements. In this paper, a new approach to prediction of earthquake induced displacements of slopes (EIDS) using hybrid support vector re...

A new smoothing method for solving ε -support vector regression (ε-SVR), tolerating a small error in fitting a given data sets nonlinearly is proposed in this study. Which is a smooth unconstrained optimization reformulation of the traditional linear programming associated with a ε-insensitive support vector regression. We term this redeveloped problem as ε-smooth support vector regression (ε-S...