Aiming at fuzzy clustering with generalized entropy, a kernel fuzzy clustering algorithm with generalized entropy based on weighted sample is presented. By introducing weight of sample into objective function for fuzzy clustering with generalized entropy, we obtain optimization problem for fuzzy clustering with generalized entropy based on weighted sample. And we use Lagrange multiplier method ...

We extend the results of Walters on the uniqueness of invariant measures with maximal entropy on compact groups to an arbitrary locally compact group. We show that the maximal entropy is attained at the left Haar measure and the measure of maximal entropy is unique.

Entropy is an important tool to describe the degree of uncertainty fuzzy sets. In this study, we first define a new entropy and distance measure in linguistic q-Rung orthopair (LIVqROF) environment, verify its correctness rationality. Secondly, LIVqROF formula effectively applied multi-attribute decision making (MADM) with unknown attribute weights, which provides idea for solving MADM problems...

Background: Science relies on experimentation to find truth. It demands that conditions remain unchanged for each repetition of an experiment. Thus, medicine relies on ‘probability theory’ based statistics and large double blind controlled randomized clinical trials. The purpose of this study is to discover measures that account for different and changing conditions of individual patients. Thes...

Abstract-This paper presents a general approach to fuzzy clustering methods. A generalised fuzzy objective function is used to combine fuzzy c-means clustering, fuzzy entropy clustering, and their extended versions into a generalised fuzzy clustering method. Some new extended versions of the above-mentioned clustering methods are proposed from this general approach. Several cluster data sets we...

Performance evaluation of various organizations especially educational institutions is a very important area of research and needs to be cultivated more. In this paper, we propose a performance evaluation for educational institutions using rough set on fuzzy approximation spaces with ordering rules and information entropy. In order to measure the performance of educational institutions, we cons...

Two Mamdani type fuzzy models (three inputs–one output and two inputs–one output) were developed to predict the permeability of compounds through human skin. The models were derived from multiple data sources including laboratory data, published data bases, published statistical models, and expert opinion. The inputs to the model include information about the compound (molecular weight and octo...

Entropy measures have been extensively used to assess heart rate variability (HRV), a noninvasive marker of cardiovascular autonomic regulation. It is yet to be elucidated whether those entropy measures can sensitively respond to changes of autonomic balance and whether the responses, if there are any, are consistent across different entropy measures. Sixteen healthy subjects were enrolled in t...

HIGHLIGHTS ► Twelve entropy indices were systematically compared in monitoring depth of anesthesia and detecting burst suppression.► Renyi permutation entropy performed best in tracking EEG changes associated with different anesthesia states.► Approximate Entropy and Sample Entropy performed best in detecting burst suppression. OBJECTIVE Entropy algorithms have been widely used in analyzing E...

The aim of this article is to solve teaching quality evaluation problems within higher education institutions. However, the evaluation process includes complex analysis of teaching resources and the learning environment. As a result, it is very difficult to evaluate teaching quality accurately and quantitatively. The research carried out quantitatively analyses and evaluates the quality of teac...