Aiming at the parameter optimization of least square support vector machine (LS-SVM), an improved quantum-behaved particle swarm optimization (IQPSO) algorithm for LS-SVM parameter selection was proposed. Based on QPSO, the algorithm optimizes particle initializing positions and improves solving speed and precision by sampling and linearizing methods. IQPSO LSSVM model was test by test function...

In hybrid simulation, the structure is divided into numerical and physical substructures to achieve more accurate responses in comparison to a full computational analysis. As a consequence of the lack of test facilities and actuators, and the budget limitation, only a few substructures can be modeled experimentally, whereas the others have to be modeled numerically. In this paper, a new hybrid ...

A new method based on least square support vector machine (LSSVM) combined with FastICA is proposed to extract the fetal electrocardiogram (FECG) from the abdominal signals of a pregnant woman. Firstly, the LSSVM is applied to estimate the maternal electrocardiogram (MECG) component in the multiplex abdominal signals. Then the optimal estimation of multiplex noise-added FECG is obtained by remo...

Abstract. Flood causes several threats with outcomes which include peril to human and animal life, damage property, adversity agricultural fields. Hence, flood prediction is highly significant for the mitigating municipal environmental damage. The aim of this study was assessing performance different machine learning methods in predicting Karkheh basin. To this, we used Support Vector Machine (...

This paper concentrates on a new procedure which experimentally recognises gears and bearings faults of a typical gearbox system using a least square support vector machine (LSSVM). Two wavelet selection criteria Maximum Energy to Shannon Entropy ratio and Maximum Relative Wavelet Energy are used and compared to select an appropriate wavelet for feature extraction. The fault diagnosis method co...

Understanding crack growth behavior in engineering components subjected to cyclic fatigue loadings is necessary for design and maintenance purpose. Fatigue crack growth (FCG) rate strongly depends on the applied loading characteristics in a nonlinear manner, and when the mechanical loadings combine with environmental attacks, this dependency will be more complicated. Since, the experimental inv...

The least square support vector machines (LSSSVM) model is a novel forecasting approach and has been successfully used to solve time series problems. However, the applications of LSSVM model in a seasonal time series forecasting has not been widely investigated. This study aims at developing a LSSVM model to forecast seasonal time series data. To assess the effectiveness of this model, the airl...