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.
Then
LSSVM was applied to train the identification model of the geometry properties.
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(.).
Therefore, the regression model of
LSSVM can be obtained as
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.