Special Issue on Aggregation Operators and Clustering

Author(s):  
Vicenç Torra ◽  
Yasuo Narukawa ◽  
Mark Daumas

This issue features decision making and other tools used in artificial intelligence applications. More specifically, the issue includes five papers focused on aggregation operators and clustering. The series starts with a paper by Yoshida on weighted quasiarithmetic means that focuses on their monotonicity viewed from utility and weighting functions. In the second paper, Nohmi, Honda and Okazaki focus on trust evaluation for networks, studying matrix operations based on t-norms and t-conorms. The authors also propose fuzzy graphs using adjacent matrices. These works are followed by three on fuzzy clustering. Kanzawa, Endo and Miyamoto present a variation of fuzzy c-means based on kernel functions in an approach developed for data with tolerance. Endo covers clustering using kernel functions. The paper is based on a fuzzy nonmetric model including pairwise constraints in the clustering process. The concluding paper also uses pairwise constraints, but within agglomerative hierarchical clustering. Hamasuna, Endo and Miyamoto include clusterwise tolerance in their mode. As the editors of this issue, we would like to thank the referees for their work in the reviews and journal editors-in-chief Profs. Toshio Fukuda and Kaoru Hirota and the journal staff for their support.

Author(s):  
Masaya Nohmi ◽  
◽  
Aoi Honda ◽  
Yoshiaki Okazaki

A new scheme for numerical trust evaluation of networks is proposed. Matrix operations based on t-norms and t-conorms are used for the evaluation. The algebraic properties of the matrix operations are studied. Fuzzy graphs, in which nodes are linked with some membership value, are proposed, using the matrices as adjacent matrices. Furthermore, the fuzzinesses of the trustability distribution are calculated.


Author(s):  
Imre J. Rudas ◽  
◽  
János Fodor

The current issue contains 12 papers presented at the <I>IEEE 9th International Conference on Intelligent Engineering Systems (INES 2005), Cruising on the Mediterranean Sea</I>, on September 16-19, 2005, and <I>3rd Serbian-Hungarian Joint Symposium on Intelligent Systems (SISY 2005), in Subotica, Serbia and Montenegro</I>, on August 31-September 1, 2005. The topics of the two conferences are very close to each other and regard Intelligent Systems both from practical and theoretical point of view. These successful conferences brought together active participants and joined researchers from several countries working on this very quickly developing, more and more important field. After a preliminary selection made by the section chairs and the International Program Committees, we have selected 12 papers to be published in extended form in the current Special Issue of the <I>Journal of Advanced Computational Intelligence and Intelligent Informatics</I>. We would like to express our thanks to our sponsors, the organizers and mainly to the participants, who made these scientific events possible. Also, we express our thanks to the Editors of the Journal of Advanced Computational Intelligence and Intelligent Informatics, for publishing this Special Issue. In the following we briefly describe each paper. A. Almeida, G. Marreiros present a model to support collaborative scheduling in complex dynamic manufacturing environments. This model considers the interaction between an Agent based Scheduling Module and a Group Decision Support Module. P. Baranyi, Z. Petres, P. L. Várkonyi, P. Korondi and Y. Yam study in their paper how the Tensor Product model transformation is capable of determining different types of convex hulls of the Linear Time Invariant models. The study is conducted through the example of the prototypical aeroelastic wing section. B. Bede, H. Nobuhara, J. Fodor and K. Hirota propose the study of the problem if usual sum and product can be substituted by max and product operations in defining approximation operators. In this sense max-product Shepard approximation operators are defined and studied. B. Benyó, P. Somogyi and B. Paláncz address the problem of classification of cerebral blood flow signals in order to identify the disorders of the cerebral circulation. The experimental results provided in the paper confirm the effectiveness of the proposed methods. J. Gáti and Gy. Kártyás propose a model based distance learning in the every day higher education practice in their contribution. They survey some important issues and methodological elements of virtual classrooms in comparison with demands for teaching procedures, programs, and materials. L. Horváth and I. J. Rudas propose a methodology for intelligent communication and change management for engineering modeling. This study motivated by increasing of importance of change management because of continuous product development. M. Maleković and M. Čubrilo describe in their contribution how to incorporate infatuation in multi-agent systems. Infatuation stands for the focusing on a single attractive or desirable characteristic of another agent and then considering the total agent as that one positive characteristic. E. Pap and M. Takács study two dimensional copulas as binary aggregation operators in their paper. Invariant copulas and an application of copulas in the theory of aggregation operators are discussed and a result on approximation of associative copulas by strict and nilpotent triangular norms is obtained. B. Reskó, Á. Csapó and P. Baranyi present in their contribution a visual cortex inspired cognitive model for contour and vertex detection. The contour detection and vertex extraction is performed by a vast network of simple units of computation simultaneously processing the visual data. The computational units are organized in a special structure, the Visual Feature Array. M. Takács addresses investigation of the problem of the approximate reasoning in the fuzzy systems, by reviewing a specific case, where the investigated structure is a real semi-ring with pseudo-operations. It is the investigation of special-type fuzzy sets, special g-generated t-norms and implications in approximate reasoning. J. K. Tar, I. J. Rudas and A. Rontó present in their paper a simple adaptive controller that creates only temporal and situation dependent system model. The temporal model can be built up and maintained step-by-step on the basis of slow elimination of fading information by the use of simple updating rules consisting of finite algebraic steps of lucid geometric interpretation. A. R. Várkonyi-Kóczy, A. Rövid and P. Várlaki present a new fuzzy based tone reproduction pre-processing algorithm which may help in developing the hardly or non-viewable features and content of the images making easier the further processing of it.


2020 ◽  
pp. 193896552094029
Author(s):  
Sean McGinley ◽  
Wei Wei ◽  
Lu Zhang ◽  
Yanyan Zheng

In response to this special issue, concerned with methods and measurements, a comprehensive review of the last 5 years of qualitative research was conducted in the top five journals that primarily publish articles pertaining to the hospitality industry. A total of 197 articles were read and analyzed for this review with a focus on the state of trustworthiness in the contemporary hospitality literature. An outline of the methods, techniques, and successes are presented in this review as are recommendations for scholars, journal editors, journal reviewers, and our partners in industry who use qualitative data for many reasons including but not limited to employee satisfaction surveys, market focus groups, and employee exit interviews. In addition, the relatively novel and nascent ideas regarding empirical rigor such as transparency and replicability are introduced to the hospitality field.


Author(s):  
Yasunori Endo ◽  

The fuzzy non metric model is a kind of clustering method in which belongingness or the membership grade of each datum to each cluster is calculated directly from dissimilarities between data, and cluster centers are not used. In this paper, we first construct a new fuzzy non metric model with entropy regularization. Second, we kernelize the proposed method by introducing kernel functions. Third, we consider pairwise constraints with the proposed method. We then confirm the above methods through some simple numerical examples.


2018 ◽  
Vol 14 (03) ◽  
pp. 403-421
Author(s):  
John N. Mordeson ◽  
Sunil Mathew ◽  
Santanu Acharjee

We introduce the idea of using aggregation operators to replace the concepts of minimum and maximum in the basic definitions and results involving fuzzy relations and fuzzy graphs. This development has begun with the replacement of minimum and maximum with [Formula: see text]-norms and [Formula: see text]-conorms, respectively. With this new theory, it will be possible to open the door to new theoretical results and at times more useful application methods. We apply our results in the areas of human trafficking and slavery.


Author(s):  
Yukihiro Hamasuna ◽  
◽  
Yasunori Endo ◽  
Sadaaki Miyamoto ◽  

This paper presents semi-supervised agglomerative hierarchical clustering algorithm using clusterwise tolerance based pairwise constraints. In semi-supervised clustering, pairwise constraints, that is, must-link and cannot-link, are frequently used in order to improve clustering properties. From that sense, we will propose another way named clusterwise tolerance based pairwise constraints to handle must-link and cannot-link constraints inL2-space. In addition, we will propose semi-supervised agglomerative hierarchical clustering algorithm based on it. We will, moreover, show the effectiveness of the proposed method through numerical examples.


2007 ◽  
Vol 15 (6) ◽  
pp. 1030-1031 ◽  
Author(s):  
Gleb Beliakov ◽  
Tomasa Calvo ◽  
Radko Mesiar

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