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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Dinh Thi Thu Huong Vu Van Truong Bui Thu Lam |
| Copyright Year | 2015 |
| Description | Author affiliation: Fac. of Inf. Technol., Le Quy Don Tech. Univ., HaNoi, Vietnam (Bui Thu Lam) || Fac. of Inf. Technol., Sai Gon Univ., Ho Chi Minh City, Vietnam (Dinh Thi Thu Huong) || Inst. of Tech. for Special, Le Quy Don Tech. Univ., HaNoi, Vietnam (Vu Van Truong) |
| Abstract | Time series forecasting is paid a considerable attention of the researchers. At present, in the field of machine learning, there are a lot of studies using an ensemble of artificial neural networks to construct the model for time series forecasting in general, and consumer price index (CPI) forecasting, in particular. However, determining the number of members of an ensemble is still debatable. This paper proposes the way of constructing a model for CPI forecasting and designing a multi-objective evolutionary algorithm in training neural networks ensembles in order to increase the diversity of the population. Two objectives of the training problem include: Mean Sum of Squared Errors and diversity. We experimented the model on three data sets and compared methods. The experimental results showed that the proposed model produced better in investigated cases. |
| Starting Page | 337 |
| Ending Page | 342 |
| File Size | 294091 |
| Page Count | 6 |
| File Format | |
| ISBN | 9781467383721 |
| ISSN | 21621020 |
| e-ISBN | 9781467383745 |
| DOI | 10.1109/ATC.2015.7388346 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2015-10-14 |
| Publisher Place | Vietnam |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Time series foracasting multi-objective evolutionary Time series analysis Sociology Artificial neural networks Evolutionary computation Predictive models ensemble Forecasting |
| Content Type | Text |
| Resource Type | Article |
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