Jan 15, 2019 · This paper suggests a fuzzy inference system (iFIS) modeling approach for interval-valued time series forecasting.
Jan 15, 2019 · This paper suggests a fuzzy inference system (iFIS) modeling approach for interval-valued time series forecasting. Interval-valued data ...
A hybrid interval‐valued time series prediction model that incorporates an intuitionistic fuzzy cognitive map and a fuzzy neural network is developed and ...
The method comprises a fuzzy rule-based framework with affine consequents which provides a (non)linear framework that processes interval-valued symbolic data.
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This paper suggests an interval fuzzy inference system (iFIS) modeling approach for interval-valued time series forecasting. Interval-valued data arise ...
This paper suggests a fuzzy rule-based approach to model and to forecast interval-valued time series. The model is a collection of functional fuzzy rules with ...
This paper proposes a fuzzy rule-based modeling approach (iFRB) for interval-valued data forecasting. iFRB is a fuzzy rule-based model with affine ...
Oct 22, 2024 · This paper proposes threshold models to analyze and forecast interval-valued time series. A relatively simple algorithm is proposed to ...
Related papers. A fuzzy inference system modeling approach for interval-valued symbolic data forecasting · Rosangela Ballini. Knowledge-Based Systems, 2018.
Oct 22, 2024 · This paper introduces an adaptive interval fuzzy modeling method using participatory learning and interval-valued stream data.