… least squares support vector machine with mixture kernels to forecast asset prices. First, a
mixture kernel function is introduced into taking full use … least squares support vector machine …

… In order to fill this gap, this study aims at proposing a novel least squares support vector
machine (LSSVM) with mixture kernel function-based integrated model for achieving the carbon …

… estimate the electricity demand. However, inaccurate demand forecasting may raise the
operating cost … be conducted forecasting through least squares support vector machine tuned by …

… As a robust intelligence classifier, support vector machine (SVM), is … squared error rather
than non-negative error in objective function. Therefore, LSSVM just needs to calculate a linear …

… BPNN), a grey seasonal least squares support vector machine (… of quarterly petroleum coke
production are 668.74, 682.68, … we calculate the parameters of the SGM (1,1) model by using …

… Among these models, support vector machine (SVM) is often used in different fields to …
and may cost more time. Hence an adaptive approach, maximum likelihood estimator (MLE) (…

… , product variety has been taken into account and sales forecasting has been performed by
using artificial intelligence to minimize error rate… used support vector machines to estimate the …

… The wavelet least squares support vector machine is used to predict carbon price. … In this
way, the nonlinear estimation function is transformed into a linear estimation function in a high-…

… of data handling (GMDH), least squares support vector machine (LSSVM), and artificial neural
network (ANN) are proposed for estimating asphaltenes adsorption onto NiO/SAPO-5, NiO…

… methods including partial least squares regression (PLSR), support vector machine (SVM),
least squares support vector machine (LS-SVM) and extreme learning machine (ELM) were …