A fuzzy controller is usually designed by formulating the knowledge of a human expert into a set of linguistic variables and fuzzy rules. As it is well known, the use of prior knowledge can dramatically improve the performance and quality…

In the information age, knowledge leads to profits, power and success. As an ancestor of data mining, machine learning has concerned itself with discovery of new knowledge on its own. This paper presents experiment results produced by genetic algorithms in…

When using tableaux algorithms to reason about Description Logics (DLs), new information is inferred from the models considered while trying to achieve knowledge satisfiability. By focusing the ontology change problem, we consider an environment where DLs are the logical formalization…

The genetic algorithms have seen applied in knowledge discovery and specially for discovering association rules. In this paper, we explore the use of di erent rule quality measures in the tness function in a genetic algorithm for discovering association rules.…

Rough Sets Theory has opened new trends for the development of the Incomplete Information Theory. Inside this one, the notion of reduct is a very significant one, but to obtain a reduct in a decision system is an expensive computing…

In this paper, the two-dimensional strip packing problem with 3-stage level patterns is tackled using genetic algorithms (GAs). We evaluate the usefulness of a greedy seeding procedure for creating the initial population, incorporating problem knowledge. This is motivated by the…

Document classification has already been widely studied. In fact, some studies compared feature selection techniques or feature space transformation whereas some others compared the performance of different algorithms. Recently, following the rising interest towards the Support Vector Machine, various studies…