This paper deals with improving the approximation capability of fuzzy systems. Fuzzy
negations produced via conical sections are a promising methodology towards better fuzzy …

Clustering is used to describe methods for grouping of unlabeled data. Clustering is an
important task in data mining to group data into meaningful subsets to retrieve information …

Density and delta-distance clustering (DDC) is an ideal clustering method that computes the
density and delta distance of data. When data derived from the two indicators are large …

The first stage in creating data-driven soft computing models is to derive information from
data, towards developing the structure of computational models. An effective way to extract …

The spectral clustering (SC) method has a good clustering effect on arbitrary structure
datasets because of its solid theoretical basis. However, the required time complexity is …

We consider possible cybernetic and systemic approaches to an interdisciplinary general
theory of change as a philosophical and scientific project. The approaches considered are …