This paper presents the application of least squares support vector machines (LS-SVMs) for automatic detection of alterations in the human electroencephalogram (EEG) activities during hypopnoea episodes. The obstructive sleep apnoea hypopnoea syndrome (OSAH) means ‘‘cessation of breath” during the sleep hours and the sufferers often experience related changes in the electrical activity of the b...

Based on the Nyström approximation and the primal-dual formulation of Least Squares Support Vector Machines (LS-SVM), it becomes possible to apply a nonlinear model to a large scale regression problem. This is done by using a sparse approximation of the nonlinear mapping induced by the kernel matrix, with an active selection of support vectors based on quadratic Renyi entropy criteria. The meth...

Because of the limited number of monitoring points on the ground, the accuracy of traditional monitoring methods using remote sensing was lower. This paper proposed to use the Least Squares Support Vector Machine (LS-SVM) theory to improve the accuracy of water quality retrieval, which is suitable for the small-sample fitting. The Radial Basic Function (RBF) was chosen as the kernel function of...

In order to effectively solve the problems of low prediction accuracy and calculation efficiency existing methods for estimating economic loss in a subway station engineering project due rainstorm flooding, new intelligent model is developed using sparrow search algorithm (SSA), least-squares support vector machine (LSSVM) mean impact value (MIV) method. First, this study, 11 input variables ar...

To meet the demand for the early location of fire in large-span space buildings, an accurate fire location method is proposed based on machine vision technology. A nonlinear implicit camera calibration method is proposed by combining an improved particle swarm optimization (PSO) method with least squares support vector machine (LS-SVM) to solve the problem that it is difficult to establish accu...