A novel method of fuzzy time series forecasting based on interval index number and membership value using support vector machine

no code implementations • 20 Oct 2020 • Kiran Bisht, Arun Kumar

There are generally, four factors that determine the performance of the forecasting method (1) number of intervals (NOIs) and length of intervals to partition universe of discourse (UOD) (2) fuzzification rules or feature representation of crisp time series (3) method of establishing fuzzy logic rule (FLRs) between input and target values (4) defuzzification rule to get crisp forecasted value.

Clustering Time Series +1