[PDF] Top 20 Improved models in fuzzy time series for forecasting

... (one-hour) forecasting Group I-II 88 ...(one-hour) forecasting Group III-IV 88 ...(six-hour) forecasting Group I-II 89 ...(six-hour) forecasting Group III-IV 89 ... See full document

... From the empirical results in the list, applying the second type gives the better forecasting accuracy rate than others. Thus, recent researches focus on the second method. There have been many methods of ... See full document

... for fuzzy time series ...weighted fuzzy time series models for Taiwan stock index (TAIEX) forecasting where it was considered by using the recurrent of ...for ... See full document

... many fuzzy time series forecasting models have studied the forecasting problem for registration number of University of ...existing forecasting models is not ...of ... See full document

... traditional forecasting methods is that they cannot contract with forecasting problems in which the historical data are represented by linguistic ...using fuzzy time series to deal with ... See full document

... adaptive time-variant model (ATVF) [12] with pso algorithm [19], [20] to improve Alabama University enrollments forecasting in this ...of fuzzy time series based on the predictive ... See full document

... used fuzzy time series models to handle load fore- casting problems ...a Time- variant Slide Fuzzy Time-series Model (TVS) for short- term load forecasting ... See full document

... the time series comprised of imprecise ...of time series the uncertainty of the individual observed values as well as the interpretation of a sequence of uncertain observed values are of ...a ... See full document

... Abstract Fuzzy time series forecasting models are used to overcome traditional time series methods when the historical data of traditional time series ... See full document

... of fuzzy time series that are linguistic ...on forecasting enrollments at University of Alabama, Forecasting AITEX Index and comment; Section 5 concludes the ... See full document

... Fuzzy Time series is being used for forecasting since last two decades for ...in Fuzzy Time Series forecasting models to get improved ...multivariate ... See full document

... or time consuming to gather and it involves generating data set by specific statistical model or using random ...and Fuzzy Time Series (FTS) model in order to identify the best model for ... See full document

... Another definition can also be termed as “series of data with time stamping on is called something as time series.” Hence in time series we capture data at specific time to get a pattern[r] ... See full document

... of fuzzy time series; time invariant model development and its implementation in forecasting the agricultural ...three models and their testing for the forecasting of Lahi ... See full document

... hybrid forecasting method (named FRGs-KM) in the first-order fuzzy time series model based on the time-invariant fuzzy logical relationship groups and K-means clustering ... See full document

... on fuzzy time series forecasting (TSF) and several studies indicating superior performance, an appropriate computationally efficient method have not been developed to predict various ... See full document

... existing fuzzy forecasting models partition historical training time series into fuzzy time series and build fuzzy-trend logical relationship groups to ... See full document

... Three fuzzy time series forecasting models applied to this study, the results are almost similar as the average forecasting error of the three models is about ... See full document

... Examining the exceedances of the 50% interval we note that while the Gaussian, GARCH and semi-parametric models yield too wide PIs, the heavy-tailed alternatives behave quite the opposite. In this respect they ... See full document

... selecting models with improved forecasting accuracies and ...out-of-sample forecasting performance evalua- ...(GARCH-type) models were applied on the returns series with respect ... See full document