The aim of the contribution is the discussion of some types and classes of means on ordinal scales, especially kernel and shift invariant ordinal means, weighted ordinal means based on weighted divisible t–conorms (t–norms) and dissimilarity based ordinal means. Moreover, several types of ordinal arithmetic means are introduced.

We propose a definition for geometric mean of k positive (semi) definite matrices. We show that our definition is the only one in the literature that has the properties that one would expect from a geometric mean, and that our geometric mean generalizes many inequalities satisfied by the geometric mean of two positive semidefinite matrices. We prove some new properties of the geometric mean of ...

In this paper we present an online unsupervised method based on clustering to find defects in concrete structures using hammering. First, the initial dataset of sound samples is roughly clustered using the k-means algorithm with the k-means++ seeding procedure in order to find the cluster best representative of the structure. Then the regular model for the hammering sound, the centroid of this ...

چکیده: در این مقاله، یک کنترل­کننده مقاوم فازی pid که به کنترل­کننده فازی pid بلادرنگ (ofpid) معروف است، برای کنترل فرکانس یک ریزشبکه در حالت جزیره­ای ارائه شده است. استراتژی کنترل­کننده پیشنهادی به­گونه­ای است که ضرایب کنترل‎کننده فازی pid در هر لحظه توسط منطق فازی تنظیم می‎شوند. جهت بهبود عملکرد کنترل‎کننده پیشنهادی، الگوریتم بهبودیافته تکامل تفاضلی (ide) پیشنهادی که دارای سرعت همگرایی مناسبی...

K-means is one of the most widely used clustering algorithms in various disciplines, especially for large datasets. However the method is known to be highly sensitive to initial seed selection of cluster centers. K-means++ has been proposed to overcome this problem and has been shown to have better accuracy and computational efficiency than k-means. In many clustering problems though –such as w...

The K-means algorithm is one of the most often used clustering techniques. However, when it comes to discovering clusters in informetric data sets that consist of non-increasingly ordered vectors of not necessarily conforming lengths, such a method cannot be applied directly. Hence, in this paper, we propose a K-means-like algorithm to determine groups of producers that are similar not only wit...