In this approach, adaptive fuzzy regression clustering (AFRC) algorithm is proposed to simultaneously define fuzzy subspaces and find the parameters in the ...

In the first-step, the Adaptive Fuzzy Regression Clustering. (AFRC), which is modified from the FCRM clustering algorithm, is employed to obtain the rough ...

In this approach, adaptive fuzzy regression clustering (AFRC) algorithm is proposed to simultaneously define fuzzy subspaces and find the parameters in the ...

Dive into the research topics of 'Adaptive fuzzy regression clustering algorithm for TSK fuzzy modeling'. Together they form a unique fingerprint. Sort by ...

This paper proposes a hybrid fuzzy rule discovery method, based on adaptive granulation of information. HGFRD is a fully data-driven approach.

Oct 22, 2024 · This study proposes a hybrid robust approach for constructing Takagi–Sugeno–Kang (TSK) fuzzy models with outliers. The approach consists of ...

This paper proposes a novel gradient-boosting-based ensemble system with a fuzzy regression tree (FRT) as its base component for regression tasks.

This paper further proposes FCM-RDpA, which improves MBGD-RDA by replacing the grid partition approach in rule initialization by fuzzy c-means clustering, and ...

Hence, a novel TSK fuzzy modeling approach with outliers is presented in this paper. In this approach, robust fuzzy regression (RFR) clustering algorithm is ...

This work extends three powerful neural network optimization techniques, i.e., minibatch gradient descent (MBGD), regularization, and AdaBound, to TSK fuzzy ...