This paper presents a comprehensive study on clustering: exiting methods and
developments made at various times. Clustering is defined as an unsupervised learning …

Solar radiation is one of the major factors for agricultural, meteorological and ecological
applications. In this study, two different optimized adaptive neuro‐fuzzy inference systems …

Investigating flow patterns in sharp bends is more essential than in mild bends due to the
complex behaviour exhibited by sharp bends. Flow variable prediction in bends is among …

A novel data knowledge representation with the combination of structure learning ability of
preprocessed collaborative fuzzy clustering and fuzzy expert knowledge of Takagi-Sugeno …

Nature-Inspired Computing: Physics and Chemistry-Based Algorithms provides a
comprehensive introduction to the methodologies and algorithms in nature-inspired …

Abstract The Metacognitive Scaffolding Learning Machine (McSLM), combining the concept
of metacognition—what-to-learn, how-to-learn, and when-to-learn, and the Scaffolding …

This study explored the potential of combining point cloud data (PCD) and data clustering
algorithms for textural damage detection of commonly seen structural elements in Taiwan …

This paper investigates the effectiveness of four different soft computing methods, namely
radial basis neural network (RBNN), adaptive neuro fuzzy inference system (ANFIS) with …

In this paper, a new method called subtractive clustering is presented to partition a power
system into areas after a disturbance occurs. Subtractive clustering is basically used as a …

The neural command from motor neurons to muscles—sometimes referred to as the neural
drive to muscle—can be identified by decomposition of electromyographic (EMG) signals …