Www.tristanfletcher.co.uk/SVM Explained.pdf. Cbio.ensmp.fr/~jvert/svn/tutorials/practical/svmbasic/svmbasic_notes.pdf. Machine learning - Support vector regression for multivariate time series prediction. Cbcl.mit.edu/people/sayan/webPub/nnsp.pdf. Chaotic time series prediction using knowledge based Green’s Kernel and least-squares support... Chaotic time series forecasting based on Cdf9/7 biorthogonal wavelet kernel support vector machine. Chaotic time series prediction based on fuzzy possibility c-mean and composite kernel support vector... A clustering based composite kernels support vector machine ensemble forecasting model is proposed for the chaotic time series prediction.
First, fuzzy possibility c-mean clustering algorithm (FPCM) is adopted to partition the input dataset into several subsets, which can overcome the drawback caused by outlier and noise in conventional fuzzy c-mean method. Then, SVMs with composite kernels that best fit partitioned subsets are constructed respectively, which hyperparameters are adaptively evolved by immune clone selection algorithm (ICGA). Finally, a fuzzy synthesis algorithm is employed to combine the outputs of submodels to obtain the final output, in which the degrees of memberships are generated by the relationship between a new input sample data and each subset center.
Application of least square support vector machine based on particle swarm optimization to chaotic t... Nonlinear prediction of chaotic time series using support vector machines.