This paper presents a hybrid approach of automatic fuzzy rule generation for on-line handwriting recognition. The fuzzy rules contain the feature information extracted from a given prototype data set. The fuzzy statistical measures and neural networks are used to select the associative features from the input symbols. The final decision is enhanced through additional combination with expert’s k...

Bousi∼Prolog is a fuzzy logic programming language whose main objective is to make flexible the query answering process. Its operational mechanism is a extension of the SLD-resolution (called weak resolution) where the classical syntactic unification algorithm has been replaced by a fuzzy one. This paper presents a generic method for the unification of linguistic terms (i.e. fuzzy sets) which i...

This paper studies the guaranteed cost control issues for the large-scale systems which are composed of Takagi-Sugeno (T-S) fuzzy subsystems with interconnections. A cost function is considered as the performance index for the system. By Lyapunov stability criterion and the parallel distributed compensation (PDC), some sufficient conditions are derived such that the large-scale fuzzy system is ...

Two major approaches to deal with randomness or impression involved in mathematical programming problems have been developed. The one is called stochastic programming, and the other is called fuzzy programming. In this paper, we focus on multiobjective integer programming problems involving random variable coefficients in constraints. Using the concept of simple recourse, such multiobjective st...

evaluative and comparative analysis among educational projects remains an issue for administration, program directors, instructors, and educational institutes. this study reports a fuzzy complexity model for educational projects, which has two primary aspects (technical aspects and transparency aspects). these aspects may not be measured precisely due to uncertain situations. therefore, a fuzzy...

 Minimum and maximum operators are two well-known t-norm and s-norm used frequently in fuzzy systems. In this paper, two different types of fuzzy inequalities are simultaneously studied where the convex combination of minimum and maximum operators is applied as the fuzzy relational composition. Some basic properties and theoretical aspects of the problem are derived and four necessary and suffi...

In this chapter we describe methods that assist the user to visually explore fuzzy clusters. We focus on a supervised approach to generate clusters for classes of interest of a given data set. The algorithm constructs local, one-dimensional neighborhood models, so-called Neighborgrams, for objects of the classes of interest that serve as a set of potential cluster candidates. The presented algo...

In this paper, we investigate the usefulness of high-resolution multispectral satellite imagery for classification of urban and suburban areas and present a fuzzy logic methodology to improve classification accuracy. Panchromatic and multispectral IKONOS image datasets are analyzed for two urban locations in this study. Both multispectral and pan-sharpened multispectral images are first classif...

Two fuzzy private matching protocols are introduced to allow a client to securely compare a list of words to a server list, and discover only those words on the server list that are similar to his, while the server learns nothing. The first protocol achieves perfect client security, while the second achieves almostprivacy and perfect server security. Both protocols are efficient in both communi...

Fuzzy set refers to the data set which does not have separate, distinct clusters, and they contain data elements whose membership degrees are between 0.0 and 1.0. Many fuzzy sets exist in the real world, and one of the important issues is to make a decision from the fuzzy sets using visual analytics tools by extracting information in the data set intuitively. To analyze the element data in fuzz...