LS-SVM Hyper-parameters Optimization Based on GWO Algorithm for Time Series Forecasting
The importance of optimizing Least Squares Support Vector Machines (LSSVM) embedded control parameters has motivated researchers to search for proficient optimization techniques. In this study, a new metaheuristic algorithm, viz., Grey Wolf Optimizer (GWO), is employed to optimize the parameter...
| Main Authors: | , , |
|---|---|
| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2015
|
| Subjects: | |
| Online Access: | http://umpir.ump.edu.my/id/eprint/11215/ http://umpir.ump.edu.my/id/eprint/11215/ http://umpir.ump.edu.my/id/eprint/11215/1/LS-SVM%20Hyper-parameters%20Optimization%20based%20on%20GWO%20Algorithm%20for%20Time%20Series%20Forecasting.pdf |