z-logo
open-access-imgOpen Access
Fuzzy Time-Series Model of Electric Power Consumption
Author(s) -
Kazuhiro Ozawa,
T. Niimura,
Tomoaki Nakashima
Publication year - 2000
Publication title -
journal of advanced computational intelligence and intelligent informatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.172
H-Index - 20
eISSN - 1343-0130
pISSN - 1883-8014
DOI - 10.20965/jaciii.2000.p0188
Subject(s) - computer science , fuzzy logic , vagueness , probabilistic logic , time series , autoregressive model , consumption (sociology) , data mining , electric power , series (stratigraphy) , statistical model , power (physics) , machine learning , artificial intelligence , econometrics , mathematics , paleontology , social science , physics , quantum mechanics , sociology , biology
In this paper, the authors present a data analysis and estimation procedure of electrical power consumption under uncertain conditions. Traditional methods are based on statistical and probabilistic approaches but it may not be quite suitable to apply purely mathematical models to the data generated by human activities such as the power consumption. The authors introduce a new approach based on possibility theory and fuzzy auto-regression, and apply it to the analysis of time-series data of electric power consumption. The proposed fuzzy auto-regression model can be constructed in simpler procedure than the conventional approaches.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here
Accelerating Research

Address

John Eccles House
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom