Decision making and technical decision analysis demand computer-aided techniques and therefore more and more support by formal techniques. In recent years fuzzy decision analysis and related techniques gained importance as an efficient method for planning and optimization applications in fields like production planning, financial and economical modeling and forecasting or classification. It is ...

Web sites become more powerful when they can adjust to their users’ needs. Web personalisation refers to adapting both the content and the presentation of web sites, so that to deliver the maximum effect to the user in the most appropriate way. A main objective of web personalisation is to adapt the presentation of the web content in a manner that increases the user’s perceived quality. This pa...

The World Wide Web has huge amount of information that is retrieved using information retrieval tool like Search Engine. Page repository of Search Engine contains the web documents downloaded by the crawler. This repository contains variety of web documents from different domains. In this paper, a technique called “Retrieval of Web documents using a fuzzy hierarchical clustering” is being propo...

In this paper a new method of rule generation for hierarchical fuzzy systems (Hierarchical Fuzzy Associative Memory, HIFAM) is described. A HIFAM is structured as a binary tree and overcomes the exponential growth of the rulebases when the number of inputs increases. The training algorithm for HIFAM is suited for approximation and classification problems. Several benchmarks demonstrate that the...

The theory of concept lattices (i.e. hierarchical structures of concepts in the sense of Port-Royal school) is approached from the point of view of fuzzy logic. The notions of partial order, lattice order, and formal concept are generalized for fuzzy setting. Presented is a theorem characterizing the hierarchical structure of formal fuzzy concepts arising in a given formal fuzzy context. Also, ...

In an earlier work, Lee et al. [1] presented a simple and fast fuzzy classifier that employed fuzzy entropy to evaluate pattern distribution information in a pattern space. In this paper, we extend his work to propose a new fuzzy classifier based on hierarchical fuzzy entropy (FC-HFE). We retained the main parts of the original structure and modified some methods (e.g., decision of the number o...

The fuzzy weighted average is widely used to solve hierarchical evaluation problems, including fuzzy consideration for the operations of scoring, weighting and aggregating. Previous works considered the fuzziness of score and weight, and used the additive function to aggregate these weighted scores. This study considers the aggregation operator also as a fuzzy variable, and uses a generalized m...

This paper investigates function approximation on discrete input spaces by both neural networks and neural-fuzzy systems. Rather than use existing neural networks for function approximation on continuous input spaces, this paper proposes, based on a hierarchical systematic perspective, four simplified approximation schemes: simplified neural networks, extended simplified neural networks, simple...

Hierarchical f u q neural networks can use less rules to model nonlinear system with high accuracy. But the structure is very complex, the normal training for hierarchical fuzzy neural networks is difficult to realize. In this paper we use backpropagation-like approach to train the membership functions. The new learning schemes employ a time-varying learning rate that is determined from input-o...

Out of the web of linked open data, comes a sense of networked “Big Data.” This large scale interconnected data is hierarchical, and often messy and full of subjective bias particularly when mass collaboration is concerned (e.g. wikipedia). In this paper we apply fuzzy set theory, specifically the X-μ approach which is shown to be more efficient than a standard fuzzy approach, to attributes wit...