Irrepressible growth of complex interconnectedness of information systems besides its obvious benefits unfortunately brought up the questions of their vulnerability. Practically universal access to computers has enabled hackers and would-be terrorists to attack information systems and critical infrastructures worldwide. Fuzzy preference relation, based on fuzzy satisfaction function is applied ...

A new technique presents to improve the performance of dynamic voltage restorer (DVR) for voltage sag mitigation. This control scheme is based on cuckoo search algorithm with tree fuzzy rule based classifier (CSA-TFRC). CSA is used for optimizing the output of TFRC so the classification output of the network is enhanced. While, the combination of cuckoo search algorithm, fuzzy and decision tree...

In order to improve the prediction precision of grain yield, the grey system theory and the fuzzy neutral network are combined to construct the combined prediction model, which is applied in predicting the grain yield. Firstly, the basic theory of the grey system theory is analyzed. Secondly, the mathematical model of fuzzy neutral network is studied, and the corresponding algorithm procedure i...

The increasing bulk of data generation in industrial and scientific applications has fostered practitioners’ interest in mining large amounts of unlabeled data in the form of continuous, high speed, and time-changing streams of information. An appealing field is association stream mining, which models dynamically complex domains via rules without assuming any a priori structure. Different from ...

Most of the proposed methods for automatic DTM reconstruction are based on parametric estimation processes with very little capabilities for reasoning and decision making. Human operators which measure DTMs solve interpretation related problems while they carry out the geometric measurements. When working with terrain often decisions have to be made which are of imprecise nature. For those prob...

Ontologies have succeeded as a knowledge representation formalism in many domains of application. Nevertheless, they are not suitable to represent vague or imprecise information. To overcome this limitation, several extensions to classical ontologies based on fuzzy logic have been proposed. Even though different fuzzy logics lead to fuzzy ontologies with very different logical properties, the c...

Various fuzzy data models such as fuzzy relational databases, fuzzy object-oriented databases, fuzzy objectrelational databases and fuzzy XML have been proposed in the literature in order to represent and process fuzzy information in databases and XML. But little work has been done in modeling fuzzy data types. Actually in the fuzzy data models, each fuzzy value is associated with a fuzzy data ...

Abstract The purpose of this paper is to extend the TOPSIS (Technique for Order Performance by Similarity to Ideal Solution) method for solving multiple attribute decision making (MADM) problems with trapezoid fuzzy linguistic variables. To begin with, this paper introduces the concept of the trapezoid fuzzy linguistic variables, and defines the distance between two trapezoid fuzzy linguistic v...

In semi supervised clustering is one of the major tasks and aims at grouping the data objects into meaningful classes (clusters) such that the similarity of objects within clusters is maximized and the similarity of objects between clusters is minimized. The dataset sometimes may be in mixed nature that is it may consist of both numeric and categorical type of data. Naturally these two types of...

While using automated learning methods, the lack of accuracy and poor knowledge generalization are both typical problems for a rule-based system obtained on a given data set. This paper introduces a new method capable of generating an accurate rule-based fuzzy inference system with parameterized consequences using an automated, off-line learning process based on multi-phase evolutionary computi...