Research Article
Hedge Algebra Approach for Semantics-Based Algorithm to Improve Result of Time Series Forecasting
@INPROCEEDINGS{10.1007/978-3-030-34365-1_15, author={Loc Vuminh and Dung Vuhoang and Dung Quachanh and Yen Phamthe}, title={Hedge Algebra Approach for Semantics-Based Algorithm to Improve Result of Time Series Forecasting}, proceedings={Context-Aware Systems and Applications, and Nature of Computation and Communication. 8th EAI International Conference, ICCASA 2019, and 5th EAI International Conference, ICTCC 2019, My Tho City, Vietnam, November 28-29, 2019, Proceedings}, proceedings_a={ICCASA \& ICTCC}, year={2019}, month={12}, keywords={Hedge algebras Fuzzy time series Forecasting Fuzziness intervals}, doi={10.1007/978-3-030-34365-1_15} }- Loc Vuminh
Dung Vuhoang
Dung Quachanh
Yen Phamthe
Year: 2019
Hedge Algebra Approach for Semantics-Based Algorithm to Improve Result of Time Series Forecasting
ICCASA & ICTCC
Springer
DOI: 10.1007/978-3-030-34365-1_15
Abstract
During the recent years, many different methods of using fuzzy time series for forecasting have been published. However, computation in the linguistic environment one term has two parallel semantics, one represented by fuzzy sets (computation-semantics) it human-imposed and the rest (context-semantic) is due to the context of the problem. If the latter semantics is not paid attention, despite the computation accomplished high level of exactly but it has been distorted about semantics. That means the result does not suitable the context of the problem. Hedge Algebras, an algebraic Approach to domains of linguistic variables, unifying the above two semantics of each term, is the basis of convenient calculation in the language environment and does not distort the semantics of terms. A new approach is proposed through a semantic-based algorithm, focus on two key steps: partitioning the universe of discourse of time series into a collection of intervals and mining fuzzy relationships from fuzzy time series, which outperforms accuracy and friendliness in computing.
