This paper presents new algorithms (Fuzzy c-Medoids or FCMdd and Robust Fuzzy c-Medoids or RFCMdd) for fuzzy clustering of relational data. The objective functions are based on selecting c representative objects (medoids) from the data set in such a way that the total fuzzy dissimilarity within each cluster is minimized. A comparison of FCMdd with the well-known Relational Fuzzy c-Means algorit...

-The traditional query in relational database is unable to satisfy the needs for dealing with fuzzy linguistic values. In this paper, a new data query technique composed of fuzzy theory and MS-SQL is provided. Here, the query can be implemented for fuzzy linguistic variables query via an interface to Microsoft ASP.NET. It is being applied to an realistic instance i.e. questions could be express...

In this paper, a subtractive relational fuzzy c-medoids clustering approach is discussed to identify web user session clusters from weblogs, based on their browsing behavior. In this approach, the internal arrangement of data along with the density of pairwise dissimilarity values is favored over arbitrary starting estimations of medoids as done in the conventional relational fuzzy c-medoids al...

In order to model multi-dimensions and multi-granularities oriented complex systems, this paper firstly proposes a kind of multi-relational Fuzzy Cognitive Map (FCM) to simulate the multi-relational system and its auto construct algorithm integrating Nonlinear Hebbian Learning (NHL) and Real Code Genetic Algorithm (RCGA). The multi-relational FCM fits to model the complex system with multi-dime...

This paper presents the development of recurrent neural network based fuzzy inference system for identification and control of dynamic nonlinear plant. The structure and algorithms of fuzzy system based on recurrent neural network are described. To train unknown parameters of the system the supervised learning algorithm is used. As a result of learning, the rules of neuro-fuzzy system are forme...

In this paper, optimization of a linear objective function with fuzzy relational inequality constraints is investigated where the feasible region is formed as the intersection of two inequality fuzzy systems and Hamacher family of t-norms is considered as fuzzy composition. Hamacher family of t-norms is a parametric family of continuous strict t-norms, whose members are decreasing functions of ...

This paper recommends a scaling factors fine-tuning fuzzy logic control approach to optimize the dynamic performance of one typical vendor managed inventory supply chain with automatic pipeline, inventory and order based production control system(VMI-APIOBPCS), based on complex fuzzy control theory. The first thing is to embed a dual-input single-output fuzzy logic controller into the system ba...

This paper deals with the design of the fuzzy expert system for processing data migration between different relational database management systems (RDBMS). At the beginning we identify current state of data migration between different RDBMS. Then we propose new approach which suggests creating of expert system as a tool for migration of database tables and their data between different RDBMS. Th...