Content-based image retrieval is one of the main research directions in information retrieval and digital library. However, the low-level image features used in traditional content-based image systems lack of semantics meanings of users. In this paper, we propose a multi-layer image data model to combine the low-level image features and high-level linguistic meanings. We analyze and represent a...

Most conventional data-mining algorithms identify the relationships among transactions using binary values and find rules at a single concept level. Transactions with quantitative values and items with taxonomic relations are, however, commonly seen in real-world applications. Besides, the taxonomic structures may also be represented in a fuzzy way. This paper thus proposes a fuzzy multiple-lev...

Fuzzy histograms are a fuzzy generalization of ordinary crisp histograms. In this paper, fuzzy histograms are analyzed statistically and are compared with other nonparametric density estimators. It turns out that fuzzy histograms can be used to combine a high level of statistical efficiency with a high level of computational efficiency.

A method for a fuzzy hierarchical structure design is presented. The proposed method uses data to design a structure of the fuzzy subsystems. The fuzzy structure is designed level by level from data thus developing an initial fuzzy model is avoided. The methods is tested on one real-world application the daily gas consumption prediction. Copyright c ©2005 IFAC

This paper discusses interpretability in two main categories of fuzzy systems fuzzy rule-based classifiers and interpolative fuzzy systems. Our goal is to show that the aspect of high level interpretability is more relevant to fuzzy classifiers, whereas fuzzy systems employed in modeling and control benefit more from low-level interpretability. We also discuss the interpretabilityaccuracy trade...

Significance and relevance of certain features are obtained by various techniques. Feature subset selection involves summarizing mutual associations between class decisions and attribute values in a pre-classified database. In this paper genetic algorithm is used to find the relevant set of features by optimizing the fitness function and using the operators like crossover and mutation. Fuzzy lo...

Expression and processing of vagueness, which has many real world applications, is not handled effectively in the conventional relational model. In this paper we investigate a fuzzy extension to the relational data model and propose three fuzzy relational query languages. ‘ho of them are the Level-l Fuzzy Relational Algebra and Level-l Fmzy Relational Calculus. They are fundamental query langua...

Data mining and knowledge discovery is described from pattern recognition point of view along with the relevance of soft computing. Key features of the computational theory of perceptions and its significance in pattern recognition and knowledge discovery problems are explained. Role of fuzzy-granulation (f-granulation) in machine and human intelligence, and its modeling through rough-fuzzy int...

In this paper, by employing a new Lyapunov functional and an elementary inequality analysis technique, some sufficient conditions are derived to ensure the existence and uniqueness of periodic oscillatory solution for fuzzy bi-directional memory (BAM) neural networks with time-varying delays, and all other solutions of the fuzzy BAM neural networks converge the uniqueness periodic solution. The...