State Forecast Method of Electronic Equipments Based on Improved HMM and LS-SVM
- Jianzhong Zhao, Wen Ye, Yong Liu, Tao Jiang
- Corresponding Author
- Jianzhong Zhao
Available Online July 2015.
- https://doi.org/10.2991/lemcs-15.2015.30How to use a DOI?
- Parameter estimation; Hidden Markov model(HMM); Least square support vector machine(LS-SVM); Multi-agent genetic algorithm (MAGA); State forecast
- For the deficiency that the traditional single forecast methods could not forecast the states of electronic equipments, a combined forecast method based on hidden Markov model (HMM) and least square support vector machine (LS-SVM) is presented. Multi-agent genetic algorithm (MAGA) is used to estimate parameters of HMM for overcoming the problem that Baum-Welch algorithm is easy to fall into local optimal solution easily. MAGA is used to estimate parameters of LS-SVM. On the base of these, the combined forecast model of electronic equipment states is established. The example analysis results shows the superiority of the combined forecast model at forecast precision, calculation speed and stability.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Jianzhong Zhao AU - Wen Ye AU - Yong Liu AU - Tao Jiang PY - 2015/07 DA - 2015/07 TI - State Forecast Method of Electronic Equipments Based on Improved HMM and LS-SVM BT - International Conference on Logistics Engineering, Management and Computer Science (LEMCS 2015) PB - Atlantis Press SN - 1951-6851 UR - https://doi.org/10.2991/lemcs-15.2015.30 DO - https://doi.org/10.2991/lemcs-15.2015.30 ID - Zhao2015/07 ER -