We present an empirical analysis of optimization techniques devised to speed up the so-called TBox classification supported by description logic systems which have to deal with very large knowledge bases (e.g. containing more than 100,000 concept introduction axioms). These techniques are integrated into the RACE architecture which implements a TBox and ABox reasoner for the description logic A...

Considering that functional magnetic resonance imaging (fMRI) signals from multiple subjects (MS) can be represented together as a sum of common and distinct rank-1 matrices, new MS dictionary learning (DL) algorithm named sparse group (common + distinct) bases (sgBACES) is proposed. Unlike existing MS-DL algorithms ignore fMRI data’s prior information, it formulated penalized plus const...

Issues related to the representation of data asssociated with terms are considered with specific reference to two knowledge representation formalisms, frames and semantic networks. Introduction Techniques developed by researchers and professional software engineers for building knowledge-based expert systems, natural language processing systems, image understanding systems and planning systems ...

optimization of reservoir parameters is an important issue in petroleum exploration and production. the ant colony optimization(aco) is a recent approach to solve discrete and continuous optimization problems. in this paper, the ant colony optimization is usedas an intelligent tool to estimate reservoir rock properties. the methodology is illustrated by using a case study on shear wave velocity...

One of the important issues when designing effective expert systems is the validation and refinement of the acquired knowledge bases. The validation and refinement problem becomes more important and more difficult when the knowledge bases of expert systems consist of uncertain rules, e.g., probabilistic rules. In this paper, we first describe one type of inconsistency of knowledge bases called ...