Decision processes for solving group decision making problems are composed of two phases: (i) aggregation and, (ii) exploitation. When experts that participate in the group decision making process are not able to express their opinions using a same expression domain, then the use of information assessed in different domains, i.e., heterogeneous information, is necessary. In these cases, the inf...

In this paper some algebraic structures for linguistic fuzzy models are defined for the first time. By definition linguistic fuzzy norm, stability of these systems can be considered. Two methods (normed-based & graphical-based) for stability analysis of linguist fuzzy systems will be presented. At the follow a new simple method for linguistic fuzzy numbers calculations is defined. At the end tw...

Lot of activities carried out in the enterprise implies Group Decision Making processes. In Group Decision Making is difficult that all experts have an exact knowledge about the problem. At the begining, Group Decision Making problems manage uncertainty with real values within a predefined range, soon interval valued approaches were proposed and more recently fuzzy-interval valued and linguisti...

Human judgment plays an important role in the rating of enterprise financial conditions. The recently developed fuzzy adaptive network (FAN), which can handle systems whose behaviour is influenced by human judgment, appears to be ideally suited for the modelling of this credit rating problem. In this paper, FAN is used to model the credit rating of small financial enterprises. To illustrate the...

Fuzzy quantifiers like ‘almost all’ and ‘about half’ abound in natural language. They are used for describing uncertain facts, quantitative relations and processes. An implementation of these quantifiers can provide expressive and easy-to-use operators for aggregation and data fusion, but also for steering the fusion process on a higher level through a safe transfer of expert-knowledge expresse...

Effective retrieval of structured documents should exploit the content and structural knowledge associated with the documents. This knowledge can be used to focus retrieval to the best entry points: document components that contain relevant information, and from which users can browse to retrieve further relevant components. To enable this, suitable representation methods must be developed. Thi...

Within the RERAU methodology, each rehabilitation criterion is assigned a grade out of 4 possible ones. This grade results from successive aggregations of performance indicators. Issues related to base data (uncertain or imprecise data) and to fusion (conflicting or reinforcing indicators) lead to envisage a fuzzy method for processing the proposed set of performance indicators. Five issues are...

We describe an approach to extract knowledge from large repositories of usability evaluation facts by using artificial intelligence techniques. Specifically, we have applied fuzzy linguistic aggregation, clustering, association mining and classifiers to different aspects of usability questionnaire analysis and design. The extracted knowledge has proven useful in computer-aided tool driven evalu...

Fuzzy linguistic quantifiers – operators intended to model vague quantifying expressions in natural language like “almost all” or “few” – have gained importance as operators for information combination and data summarisation. They are particularly appealing because of their ease-of-use: people are familiar with these operators, which can be applied for technical aggregation purposes in the same...

Multicriteria decision-making (MCDM) problems often involve a complex decision process in which multiple requirements and fuzzy conditions have to be taken into consideration simultaneously. The existing approaches for solving this problem in a fuzzy environment are complex. Combining the concepts of grey relation and pairwise comparison, a new fuzzy MCDM method is proposed. First, the fuzzy an...