A Multivariate Heuristic Model for Fuzzy Time-Series Forecasting

Kun‐Huang Huarng · Tiffany Hui‐Kuang Yu · Yu Wei Hsu

175 citations0/0 files storedIEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)

No readable copy stored yet — this record is metadata only.

No open-access location is known for this record yet.

Literature note Cite in a project Citation map

Forecasting Techniques and Applications Fuzzy Logic and Control Systems Fuzzy Systems and Optimization

Abstract

Fuzzy time-series models have been widely applied due to their ability to handle nonlinear data directly and because no rigid assumptions for the data are needed. In addition, many such models have been shown to provide better forecasting results than their conventional counterparts. However, since most of these models require complicated matrix computations, this paper proposes the adoption of a multivariate heuristic function that can be integrated with univariate fuzzy time-series models into multivariate models. Such a multivariate heuristic function can easily be extended and integrated with various univariate models. Furthermore, the integrated model can handle multiple variables to improve forecasting results and, at the same time, avoid complicated computations due to the inclusion of multiple variables.

Paper brief

Loading…

Cite this work

Citation unavailable for this work.

BibTeX RIS CSL-JSON

No public copy is stored for this record, so only the metadata is cited.

Citations in this library

Citation map →

Stored only when both papers are in the corpus — 175 citations exist upstream.

References

1993Forecasting enrollments with fuzzy time series — Part I 1996Forecasting enrollments based on fuzzy time series 1994Forecasting enrollments with fuzzy time series — part II 2001Effective lengths of intervals to improve forecasting in fuzzy time series 2002FORECASTING ENROLLMENTS BASED ON HIGH-ORDER FUZZY TIME SERIES 2004Weighted fuzzy time series models for TAIEX forecasting 2001Heuristic models of fuzzy time series for forecasting 2000Temperature prediction using fuzzy time series

Cited by

2009Prediction-based portfolio optimization model using neural networks 2013TAIEX forecasting based on fuzzy time series, particle swarm optimization techniques and support vector machines 2016A survey on forecasting of time series data 2011Fuzzy forecasting based on high-order fuzzy logical relationships and automatic clustering techniques 2014Fuzzy Forecasting Based on Two-Factors Second-Order Fuzzy-Trend Logical Relationship Groups and the Probabilities of Trends of Fuzzy Logical Relationships

Explore the map →

Papers that cite the same references — the relational fallback while embeddings are still backfilling.

Imported from OpenAlex (CC0) — nothing here is generated.