Graphical models for hierarchical computations in the analysis and design of replications.
Gröbner bases in geometry theorem proving and simplest degeneracy conditions.
Grounding and extracting modal responses in cognitive agents: 'AND' query and states of incomplete knowledge
In this study an original way of modeling language grounding and generation for a simple set of language responses is presented. It is assumed that the language is used by a cognitive agent and consists of a few modal belief and possibility formulas that are used by this agent to communicate its opinions on the current state of an object. The cognitive agent is asked a simple AND query and the language is tailored to this situation. The agent's knowledge bases are characterized by certain incompleteness...
GTES : une méthode de simulation par jeux et apprentissage pour l'analyse des systèmes d'acteurs
Cet article décrit une approche de la modélisation d'un système d'acteurs, particulièrement adaptée à la modélisation des entreprises, fondée sur la théorie des jeux [11] et sur l'optimisation par apprentissage du comportement de ces acteurs. Cette méthode repose sur la combinaison de trois techniques : la simulation par échantillonnage (Monte-Carlo), la théorie des jeux pour ce qui concerne la recherche d'équilibre entre les stratégies, et les méthodes heuristiques d'optimisation locale,...
Guest Editorial: Fuzzy logic and soft computing in an effective and efficient processing of imperfect information - in memoriam Ashley Morris
Guest Editors' Introduction
GUHA - metoda systematického vyhledávání hypotéz
GUHA - metoda systematického vyhledávání hypotéz. II
Guided Local Search for query reformulation using weight propagation
A new technique for query reformulation that assesses the relevance of retrieved documents using weight propagation is proposed. The technique uses a Guided Local Search (GLS) in conjunction with the latent semantic indexing model (to semantically cluster documents together) and Lexical Matching (LM). The GLS algorithm is used to construct a minimum spanning tree that is later employed in the reformulation process. The computations done for Singular Value Decomposition (SVD), LM and the minimum...
Handwritten digit recognition by combined classifiers
Classifiers can be combined to reduce classification errors. We did experiments on a data set consisting of different sets of features of handwritten digits. Different types of classifiers were trained on these feature sets. The performances of these classifiers and combination rules were tested. The best results were acquired with the mean, median and product combination rules. The product was best for combining linear classifiers, the median for -NN classifiers. Training a classifier on all features...
Hard and fuzzy classification within the framework of hierarchical and optimization clustering
Hausdorff Distances for Searching in Binary Text Images
This work has been partially supported by Grant No. DO 02-275, 16.12.2008, Bulgarian NSF, Ministry of Education and Science.Hausdorff distance (HD) seems the most efficient instrument for measuring how far two compact non-empty subsets of a metric space are from each other. This paper considers the possibilities provided by HD and some of its modifications used recently by many authors for resemblance between binary text images. Summarizing part of the existing word image matching methods, relied...
Heuristic Approach to Train Rescheduling
Heuristic for avoiding skolemization in theorem proving.
Heuristic search algorithms on directed trees
Hierarchical text categorization using fuzzy relational thesaurus
Text categorization is the classification to assign a text document to an appropriate category in a predefined set of categories. We present a new approach for the text categorization by means of Fuzzy Relational Thesaurus (FRT). FRT is a multilevel category system that stores and maintains adaptive local dictionary for each category. The goal of our approach is twofold; to develop a reliable text categorization method on a certain subject domain, and to expand the initial FRT by automatically added...
Highly robust training of regularizedradial basis function networks
Radial basis function (RBF) networks represent established tools for nonlinear regression modeling with numerous applications in various fields. Because their standard training is vulnerable with respect to the presence of outliers in the data, several robust methods for RBF network training have been proposed recently. This paper is interested in robust regularized RBF networks. A robust inter-quantile version of RBF networks based on trimmed least squares is proposed here. Then, a systematic comparison...
Histoire et préhistoire de l'analyse des données
Histoire et préhistoire de l'analyse des données
Histoire et préhistoire de l'analyse des données