LSSVM

AcronymDefinition
LSSVMLeast Squares Support Vector Machine
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References in periodicals archive ?
The forecast results of different seasons show that both the RBF neural network prediction model and the LSSVM prediction model wind speed prediction model can describe the trend of the original wind speed series, but the values of the LSSVM prediction model are more close to the original wind speed data.
Huang, "A novel spatiotemporal LSSVM method for complex distributed parameter systems with applications to curing thermal process," IEEE Transactions on Industrial Informatics, vol.
Moreover, it is only necessary to compute the dot product of nonlinear mapping functions during the model construction and prediction phase of LSSVM. The result of this dot product of nonlinear mapping functions is the kernel function K(.).
Li, "Prediction of the temperature in a Chinese solar greenhouse based on LSSVM optimized by improved PSO," Computers and Electronics in Agriculture, vol.
There are a variety of methods for statistical downscaling [5], for example, the Delta Method (DM), Bias-Correction Method (BCM), Constructed Analogs Method (CAM), Localized Constructed Analogs Method (LOCA), Artificial Neural Networks (ANNs), Least Squares Support Vector Machines (LSSVM), nonparametric kernel regression (NKR) [8-10], and so forth.
So far, researchers have come up with many methods to build the soft sensing model, such as neural networks [5], the support vector machines (SVM) [6], partial least squares [7], and least squares support vector machine (LSSVM) [8]; these methods are aimed at specific problem.
Chang, "Forecasting fossil fuel energy consumption for power generation using QHSA-based LSSVM model," Energies, vol.
Deng and Yeh [46] showed the use of LSSVM (LS, least squares) model in the cost prediction process.
[5] developed a prediction model based on the least square support vector machine (LSSVM) to detect the pullout capacity of small anchors; and they concluded that the LSSVM performs better than the ANN [5].
Wind Power Grid Connected Capacity Prediction Using LSSVM Optimized by the Bat Algorithm.