In clustering process, fuzzy partition performs better than hard partition when the boundaries
between clusters are vague. Whereas, traditional fuzzy clustering algorithms produce less …

Automatic art analysis employs different image processing techniques to classify and
categorize works of art. When working with artistic images, we need to take into account …

As an important technique of data analysis, clustering plays an important role in finding the
underlying pattern structure embedded in unlabeled data. Clustering algorithms that need to …

Black-box models play an important role in advancing the blast furnace modeling
technologies for control purposes. To further enhance their practical applications, this paper …

The fuzzy rule-based classification system (FRBCS) is a popular tool for classification
problems due to its interpretability and comprehensibility. As an extension of fuzzy numbers …

Clustering is the process of dividing a collection of physical or abstract objects into several
classes composed of similar objects. Now there are many clustering algorithms with superior …

Takagi–Sugeno–Kang (TSK) fuzzy inference has been widely used in approximating
uncertain nonlinear systems because of its high interpretability and precision. However, TSK …

Robust fuzzy clustering models for fuzzy data are proposed. In particular, using a
“Partitioning Around Medoids”(PAM) approach, first a timid robustification of fuzzy clustering …

Yield forecasting is an important task for the manufacturer of semiconductors. Owing to the
uncertainty in yield learning, it is, however, often difficult to make precise and accurate yield …

Achievement of sustainable privacy preservation is mostly very challenging in a resource
shared computer environment. This challenge demands a dedicated focus on the …