The Fuzzy Logic and system are widely used in many fields during the last decades. Many tools and methods are developed to mine the data in the interdisciplinary science, which witnesses the novel discovery in Science and new technologies in Engineering. To exchange the ideas and research in East Asia, the 2015 International Conference on Fuzzy System and Data Mining (FSDM 2015) is held during ...

Fuzzy Sets theory has been applied in many fields to handle uncertainty, which can be reflected on the membership degree of the objects belonging to a set. Moreover, Hesitant Fuzzy Sets are useful whenever there is indecision among several possible values for the preferences over objects in the process of decision-making. In this sense, the aim of this work is to consider the notion of aggregat...

Explaining emergence is a difficult work such that there are many arguments on what it is or how it can be explained. Nonetheless, it is frequently referred in many fields such as behavior based robotics, artificial life, and complex systems without any on formal definition. In this paper, we develop a fuzzy logic controller for a simulated mobile robot with genetic algorithm and analyze behavi...

There are various methods regarding project selection in different fields. This paper deals with an actual application of construction project selection, using two aggregation operators. First, the opinion of experts is used in a model of group decision making called intuitionistic fuzzy TOPSIS IFT . Secondly, project evaluation is formulated by dynamic intuitionistic fuzzy weighted averaging D...

Since its development attribute exploration was successfully applied in different fields, proving itself as a strong tool for knowledge acquisition. However, the disadvantage of this method is that it can be applied only for binary data. The growing number of applications of fuzzy logic in numerous domains including formal concept analysis makes it a natural wish to generalise the powerful tech...

The industrial applications of fuzzy processors are increasing mainly in control and pattern recognition fields. Some of these applications require high speed that can not be obtained by standard commercial fuzzy processors. This paper describes the architecture of a very small size high speed fuzzy chip with two inputs and one output. The input sample rate of 80 ns (4 clock cycles at 50 MHz) i...

Machine learning, data mining, and several related research areas are concerned with methods for the automated induction of models and the extraction of interesting patterns from empirical data. Automated knowledge acquisition of that kind has been an essential aspect of artificial intelligence since a long time and has more recently also attracted considerable attention in the fuzzy sets commu...

This special session collects papers that reflect current progress in the research about fuzzy and intelligent systems. We hope those papers accepted can provide some milestones for the related research fields and also give ideas for further exploration in their research issues. Totally, nine papers are accepted in this session. Among them, six papers are about fuzzy theories and the related ap...

In this paper we study a large class of renormalization transformations of measures on lattices. An image of a Gibbs measure under such transformation is called a fuzzy Gibbs measure. Transformations of this type and fuzzy Gibbs measures appear naturally in many fields. Examples include the hidden Markov processes (HMP), memoryless channels in information theory, continuous block factors of sym...