Additive manufacturing with an emphasis on 3D printing has recently become popular due
to its exceptional advantages over conventional manufacturing processes. However, 3D …

The Fuzzy c-means is one of the most popular ongoing area of research among all types of
researchers including Computer science, Mathematics and other areas of engineering, as …

The main reason of the extensive usage of the fuzzy systems in many branches of science is
their approximation ability. In this paper, an interval type-3 fuzzy system (IT3FS) is proposed …

Clustering is a fundamental data analysis method. It is widely used for pattern recognition,
feature extraction, vector quantization (VQ), image segmentation, function approximation …

Conventional model-based data processing methods are computationally expensive and
require experts' knowledge for the modelling of a system. Neural networks are a model-free …

Clustering is an important unsupervised classification technique where data points are
grouped such that points that are similar in some sense belong to the same cluster. Cluster …

In this study, we design polynomial-based radial basis function neural networks (P-RBF
NNs) based on a fuzzy inference mechanism. The essential design parameters (including …

A new hybrid self-adaptive training approach-based radial basis function (RBF) neural
network for power transformer fault diagnosis is presented in this paper. The proposed …

We propose an integrated mechanism for discarding derogatory features and extraction of
fuzzy rules based on an interval type-2 neural fuzzy system (NFS)-in fact, it is a more general …

Cycle time forecasting (CTF) is one of the most crucial issues for production planning to
keep high delivery reliability in semiconductor wafer fabrication systems (SWFS). This paper …