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A Novel Stochastic Fuzzy Time Series Forecasting Model Based on a New Partition Method
16 references·0 citing·27 second hop
A Novel Stochastic Fuzzy Time Series Forecasting Model Based on a New Partition Method (2021)A Novel Stochastic Fuzzy Time Series Fore…A fuzzy time series approach based on weights determined by the number of recurrences of fuzzy relations (2013)A fuzzy time series approach …Temperature prediction and TAIFEX forecasting based on fuzzy relationships and MTPSO techniques☆ (2009)Temperature prediction and TA…TAIFEX and KOSPI 200 forecasting based on two-factors high-order fuzzy time series and particle swarm optimization (2009)TAIFEX and KOSPI 200 forecast…Finding an optimal interval length in high order fuzzy time series (2009)Finding an optimal interval l…An improved method for forecasting enrollments based on fuzzy time series and particle swarm optimization (2008)An improved method for foreca…A computational method of forecasting based on fuzzy time series (2008)A computational method of for…Ratio-based lengths of intervals to improve fuzzy time series forecasting (2006)Ratio-based lengths of interv…Multi-attribute fuzzy time series method based on fuzzy clustering (2006)Multi-attribute fuzzy time se…Forecasting enrollments using high-order fuzzy time series and genetic algorithms (2006)Forecasting enrollments using…A New Method to Forecast Enrollments Using Fuzzy Time Series (2004)A New Method to Forecast Enro…Effective lengths of intervals to improve forecasting in fuzzy time series (2001)Effective lengths of interval…FUZZY SETS (1996)FUZZY SETSFuzzy sets (1996)Fuzzy setsForecasting enrollments based on fuzzy time series (1996)Forecasting enrollments based…Forecasting enrollments with fuzzy time series — Part I (1993)Forecasting enrollments with …Time Series Analysis, Forecasting and Control. (1971)Time Series Analysis, Forecas…Fuzzy sets (1965)The concept of a linguistic variable and its application to approximate reasoning—II (1975)FORECASTING ENROLLMENTS BASED ON HIGH-ORDER FUZZY TIME SERIES (2002)Weighted fuzzy time series models for TAIEX forecasting (2004)Forecasting enrollments with fuzzy time series — part II (1994)The application of neural networks to forecast fuzzy time series (2005)THE DEMAND FOR HIGHER EDUCATION AND INSTITUTIONAL ENROLLMENT FORECASTING (1979)Applied Economic Forecasting (1967)Introductory Econometrics for Finance (2008)A neural network-based fuzzy time series model to improve forecasting (2009)A hybrid fuzzy time series model based on granular computing for stock price forecasting (2014)A simple method of forecasting based on fuzzy time series (2006)Pattern discovery of fuzzy time series for financial prediction (2006)TAIEX Forecasting Based on Fuzzy Time Series and Fuzzy Variation Groups (2010)Improvement of Auto-Regressive Integrated Moving Average models using Fuzzy logic and Artificial Neural Networks (ANNs) (2008)Digital currency forecasting with chaotic meta-heuristic bio-inspired signal processing techniques (2019)TAIEX forecasting based on fuzzy time series, particle swarm optimization techniques and support vector machines (2013)Fuzzy time series forecasting based on fuzzy logical relationships and similarity measures (2015)Extensions of the TOPSIS for group decision-making under fuzzy environment (2000)Science mapping software tools: Review, analysis, and cooperative study among tools (2011)Set-Theoretic Methods for the Social Sciences (2012)Political Parties and Macroeconomic Policy (1977)Do Stock Prices Move Too Much to be Justified by Subsequent Changes in Dividends? (1980)Understanding spurious regressions in econometrics (1986)Multi-criteria decision making in Pythagorean fuzzy environment (2019)Analyzing barriers for the adoption of circular economy in the manufacturing sector (2021)The impact of artificial intelligence capabilities on servitization: The moderating role of absorptive capacity-A dynamic capabilities perspective (2022)
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  • 2009TAIFEX and KOSPI 200 forecasting based on two-factors high-order fuzzy time series and particle swarm optimization

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95 cited
  • 2013A fuzzy time series approach based on weights determined by the number of recurrences of fuzzy relations56 cited
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