| DC Field | Value | Language |
|---|
| dc.contributor.author | Kashpruk, Nataliia | |
| dc.contributor.author | Walaszek-Babiszewska, Anna | |
| dc.contributor.author | Rydel, Marek | |
| dc.coverage.temporal | 21-25 August 2018, Lviv | |
| dc.date.accessioned | 2020-06-19T12:05:36Z | - |
| dc.date.available | 2020-06-19T12:05:36Z | - |
| dc.date.created | 2018-02-28 | |
| dc.date.issued | 2018-02-28 | |
| dc.identifier.citation | Kashpruk N. On the Equivalence between AR Family Time Series Models and Fuzzy Models in Signal Processing / Nataliia Kashpruk, Anna Walaszek-Babiszewska, Marek Rydel // Data stream mining and processing : proceedings of the IEEE second international conference, 21-25 August 2018, Lviv. — Львів : Lviv Politechnic Publishing House, 2018. — P. 331–335. — (Hybrid Systems of Computational Intelligence). | |
| dc.identifier.isbn | © Національний університет „Львівська політехніка“, 2018 | |
| dc.identifier.isbn | © Національний університет „Львівська політехніка“, 2018 | |
| dc.identifier.uri | https://ena.lpnu.ua/handle/ntb/52517 | - |
| dc.description.abstract | In the paper an advanced analysis of the
relationships between statistical Autoregressive (AR) type
models and fuzzy models have been presented. The examined
family of AR type models includes Autoregressive models of
order p, AR(p), Threshold AR (TAR) as well as Smooth
Transition Autoregressive (STAR) models. On the other hand,
fuzzy models representing different approach, characteristic
for Computational Intelligence technics, have been tested for
time series analysis and forecasting. The data have been taken
from financial market. The research can enrich knowledge
which is useful for experts using both approaches to modelling. | |
| dc.format.extent | 331-335 | |
| dc.language.iso | en | |
| dc.publisher | Lviv Politechnic Publishing House | |
| dc.relation.ispartof | Data stream mining and processing : proceedings of the IEEE second international conference, 2018 | |
| dc.title | On the Equivalence between AR Family Time Series Models and Fuzzy Models in Signal Processing | |
| dc.type | Conference Abstract | |
| dc.rights.holder | © Національний університет “Львівська політехніка”, 2018 | |
| dc.contributor.affiliation | Opole University of Technology | |
| dc.format.pages | 5 | |
| dc.identifier.citationen | Kashpruk N. On the Equivalence between AR Family Time Series Models and Fuzzy Models in Signal Processing / Nataliia Kashpruk, Anna Walaszek-Babiszewska, Marek Rydel // Data stream mining and processing : proceedings of the IEEE second international conference, 21-25 August 2018, Lviv. — Lviv Politechnic Publishing House, 2018. — P. 331–335. — (Hybrid Systems of Computational Intelligence). | |
| dc.relation.references | [1] G. Box and G. Jenkins, Time Series Analysis: Forecasting and Control, San Francisco: Holden-Day, 1970. | |
| dc.relation.references | [2] J. L. Aznarte and J. M. Benitez, “The links between statistical and fuzzy models for time series analysis and forecasting,” in: Time Series Analysis, Modeling and Applications; A Computational Intelligence Perspective, W. Pedrycz and Shyi-Ming Chen, Eds. Intelligence Systems Reference Library, vol. 47, Springer, pp. 1-30, 2013. | |
| dc.relation.references | [3] E. H. Mamdani and S. Assilan, “An experiment in linguistic synthesis with a fuzzy logic controller,” International Journal of ManMachine Studies, 20(2), pp. 1-13, 1970. | |
| dc.relation.references | [4] R. R. Yager and D. P. Filev, Essentials of Fuzzy Modeling and Control, John Wiley & Sons, Inc. 1994. | |
| dc.relation.references | [5] T. Takagi and M. Sugeno, “Fuzzy identification of systems and its applications to modeling and control,” IEEE Transactions on Systems, Man and Cybernetics, 15, pp.116-132, 1985. | |
| dc.relation.referencesen | [1] G. Box and G. Jenkins, Time Series Analysis: Forecasting and Control, San Francisco: Holden-Day, 1970. | |
| dc.relation.referencesen | [2] J. L. Aznarte and J. M. Benitez, "The links between statistical and fuzzy models for time series analysis and forecasting," in: Time Series Analysis, Modeling and Applications; A Computational Intelligence Perspective, W. Pedrycz and Shyi-Ming Chen, Eds. Intelligence Systems Reference Library, vol. 47, Springer, pp. 1-30, 2013. | |
| dc.relation.referencesen | [3] E. H. Mamdani and S. Assilan, "An experiment in linguistic synthesis with a fuzzy logic controller," International Journal of ManMachine Studies, 20(2), pp. 1-13, 1970. | |
| dc.relation.referencesen | [4] R. R. Yager and D. P. Filev, Essentials of Fuzzy Modeling and Control, John Wiley & Sons, Inc. 1994. | |
| dc.relation.referencesen | [5] T. Takagi and M. Sugeno, "Fuzzy identification of systems and its applications to modeling and control," IEEE Transactions on Systems, Man and Cybernetics, 15, pp.116-132, 1985. | |
| dc.citation.conference | IEEE second international conference "Data stream mining and processing" | |
| dc.citation.spage | 331 | |
| dc.citation.epage | 335 | |
| dc.coverage.placename | Львів | |
| Appears in Collections: | Data stream mining and processing : proceedings of the IEEE second international conference
|
