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Fuzzy time series forecasting based on fuzzy logical relationships and similarity measures
16 references·16 citing·9 second hopsampled
Fuzzy time series forecasting based on fuzzy logical relationships and similarity measures (2015)Fuzzy time series forecasting based on fu…Ratio-based lengths of intervals to improve fuzzy time series forecasting (2006)Ratio-based lengths of interv…Handling forecasting problems based on two-factors high-order fuzzy time series (2006)Handling forecasting problems…Forecasting enrollments using high-order fuzzy time series and genetic algorithms (2006)Forecasting enrollments using…The application of neural networks to forecast fuzzy time series (2005)The application of neural net…Weighted fuzzy time series models for TAIEX forecasting (2004)Weighted fuzzy time series mo…FORECASTING ENROLLMENTS BASED ON HIGH-ORDER FUZZY TIME SERIES (2002)FORECASTING ENROLLMENTS BASED…Heuristic models of fuzzy time series for forecasting (2001)Heuristic models of fuzzy tim…Effective lengths of intervals to improve forecasting in fuzzy time series (2001)Effective lengths of interval…Temperature prediction using fuzzy time series (2000)Temperature prediction using …Handling forecasting problems using fuzzy time series (1998)Handling forecasting problems…Fuzzy sets (1996)Fuzzy setsForecasting enrollments based on fuzzy time series (1996)Forecasting enrollments based…Forecasting enrollments with fuzzy time series — part II (1994)Forecasting enrollments with …A comparison of fuzzy forecasting and Markov modeling (1994)A comparison of fuzzy forecas…Forecasting enrollments with fuzzy time series — Part I (1993)Forecasting enrollments with …Fuzzy sets (1965)Fuzzy setsA novel dice similarity measure for IFSs and its applications in pattern and face recognition (2020)A novel dice similarity measu…Novel distance measures for Pythagorean fuzzy sets with applications to pattern recognition problems (2019)Novel distance measures for P…Interval-valued intuitionistic fuzzy multiple attribute decision making based on nonlinear programming methodology and TOPSIS method (2019)Interval-valued intuitionisti…Fuzzy time series forecasting based on proportions of intervals and particle swarm optimization techniques (2019)Fuzzy time series forecasting…Fuzzy forecasting based on linear combinations of independent variables, subtractive clustering algorithm and artificial bee colony algorithm (2019)Fuzzy forecasting based on li…Designing fuzzy time series forecasting models: A survey (2019)Designing fuzzy time series f…A study on leading machine learning techniques for high order fuzzy time series forecasting (2019)A study on leading machine le…A novel high-order fuzzy time series forecasting method based on probabilistic fuzzy sets (2019)A novel high-order fuzzy time…A deep learning approach for financial market prediction: utilization of Google trends and keywords (2019)A deep learning approach for …Prediction of TAIEX based on hybrid fuzzy time series model with single optimization process (2018)Prediction of TAIEX based on …Forecasting energy demand in China and India: Using single-linear, hybrid-linear, and non-linear time series forecast techniques (2018)Forecasting energy demand in …A novel data partitioning and rule selection technique for modeling high-order fuzzy time series (2017)A novel data partitioning and…Fuzzy time series forecasting method based on hesitant fuzzy sets (2016)Fuzzy time series forecasting…Fuzzy time series forecasting based on optimal partitions of intervals and optimal weighting vectors (2016)Fuzzy time series forecasting…Fuzzy forecasting based on two-factors second-order fuzzy-trend logical relationship groups, similarity measures and PSO techniques (2016)Fuzzy forecasting based on tw…An intelligent pattern recognition model for supporting investment decisions in stock market (2016)An intelligent pattern recogn…The concept of a linguistic variable and its application to approximate reasoning—II (1975)Forecasting stock markets using wavelet transforms and recurrent neural networks: An integrated system based on artificial bee colony algorithm (2010)Digital currency forecasting with chaotic meta-heuristic bio-inspired signal processing techniques (2019)Extensions of the TOPSIS for group decision-making under fuzzy environment (2000)An approach for detecting, quantifying, and visualizing the evolution of a research field: A practical application to the Fuzzy Sets Theory field (2010)Science mapping software tools: Review, analysis, and cooperative study among tools (2011)Family resemblances: Studies in the internal structure of categories (1975)Basic objects in natural categories (1976)Soft set theory—First results (1999)
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References

  • 1965Fuzzy sets67,827 cited
  • 1996Fuzzy sets46,880 cited
  • 1993Forecasting enrollments with fuzzy time series — Part I1,255 cited
  • 1996Forecasting enrollments based on fuzzy time series1,186 cited
  • 1994Forecasting enrollments with fuzzy time series — part II789 cited
  • 2001Effective lengths of intervals to improve forecasting in fuzzy time series583 cited
  • 2002FORECASTING ENROLLMENTS BASED ON HIGH-ORDER FUZZY TIME SERIES518 cited
  • 2004Weighted fuzzy time series models for TAIEX forecasting463 cited
  • 2001Heuristic models of fuzzy time series for forecasting440 cited
  • 2000Temperature prediction using fuzzy time series400 cited
  • 1998Handling forecasting problems using fuzzy time series368 cited
  • 2005The application of neural networks to forecast fuzzy time series308 cited
  • 2006Ratio-based lengths of intervals to improve fuzzy time series forecasting306 cited
  • 1994A comparison of fuzzy forecasting and Markov modeling269 cited
  • 2006Forecasting enrollments using high-order fuzzy time series and genetic algorithms252 cited
  • 2006Handling forecasting problems based on two-factors high-order fuzzy time series

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246 cited

Cited by

  • 2018Forecasting energy demand in China and India: Using single-linear, hybrid-linear, and non-linear time series forecast techniques194 cited
  • 2019Interval-valued intuitionistic fuzzy multiple attribute decision making based on nonlinear programming methodology and TOPSIS method140 cited
  • 2016Fuzzy time series forecasting based on optimal partitions of intervals and optimal weighting vectors130 cited
  • 2019Designing fuzzy time series forecasting models: A survey129 cited
  • 2016Fuzzy forecasting based on two-factors second-order fuzzy-trend logical relationship groups, similarity measures and PSO techniques127 cited
  • 2016Fuzzy time series forecasting method based on hesitant fuzzy sets126 cited
  • 2019Fuzzy time series forecasting based on proportions of intervals and particle swarm optimization techniques114 cited
  • 2016An intelligent pattern recognition model for supporting investment decisions in stock market99 cited
  • 2019A study on leading machine learning techniques for high order fuzzy time series forecasting86 cited
  • 2019Novel distance measures for Pythagorean fuzzy sets with applications to pattern recognition problems74 cited
  • 2019Fuzzy forecasting based on linear combinations of independent variables, subtractive clustering algorithm and artificial bee colony algorithm64 cited
  • 2017A novel data partitioning and rule selection technique for modeling high-order fuzzy time series60 cited
  • 2018Prediction of TAIEX based on hybrid fuzzy time series model with single optimization process56 cited
  • 2020A novel dice similarity measure for IFSs and its applications in pattern and face recognition53 cited
  • 2019A deep learning approach for financial market prediction: utilization of Google trends and keywords52 cited
  • 2019A novel high-order fuzzy time series forecasting method based on probabilistic fuzzy sets39 cited