All a b c d e f g h i j k l m n o p q r s t u v w x y z Other

Previous Page 2

Displaying 21 – 36 of 36

Showing per page

Evolving co-adapted subcomponents in assembler encoding

Tomasz Praczyk (2007)

International Journal of Applied Mathematics and Computer Science

The paper presents a new Artificial Neural Network (ANN) encoding method called Assembler Encoding (AE). It assumes that the ANN is encoded in the form of a program (Assembler Encoding Program, AEP) of a linear organization and of a structure similar to the structure of a simple assembler program. The task of the AEP is to create a Connectivity Matrix (CM) which can be transformed into the ANN of any architecture. To create AEPs, and in consequence ANNs, genetic algorithms (GAs) are used. In addition...

Experimental analysis of some computation rules in a simple parallel reasoning system for the ALC description logic

Adam Meissner (2011)

International Journal of Applied Mathematics and Computer Science

A computation rule determines the order of selecting premises during an inference process. In this paper we empirically analyse three particular computation rules in a tableau-based, parallel reasoning system for the ALC description logic, which is built in the relational programming model in the Oz language. The system is constructed in the lean deduction style, namely, it has the form of a small program containing only basic mechanisms, which assure soundness and completeness of reasoning. In...

Experiments with two Approaches for Tracking Drifting Concepts

Koychev, Ivan (2007)

Serdica Journal of Computing

This paper addresses the task of learning classifiers from streams of labelled data. In this case we can face the problem that the underlying concepts can change over time. The paper studies two mechanisms developed for dealing with changing concepts. Both are based on the time window idea. The first one forgets gradually, by assigning to the examples weight that gradually decreases over time. The second one uses a statistical test to detect changes in concept and then optimizes the size of the...

Experiments with variants of ant algorithms.

Thomas Stützle, Sebastian Linke (2002)

Mathware and Soft Computing

A number of extensions of Ant System, the first ant colony optimization (ACO) algorithm, were proposed in the literature. These extensions typically achieve much improved computational results when compared to the original Ant System. However, many design choices of Ant System are left untouched including the fact that solutions are constructed, that real-numbers are used to simulate pheromone trails, and that explicit pheromone evaporation is used. In this article we experimentally investigate...

Exploiting tensor rank-one decomposition in probabilistic inference

Petr Savický, Jiří Vomlel (2007)

Kybernetika

We propose a new additive decomposition of probability tables – tensor rank-one decomposition. The basic idea is to decompose a probability table into a series of tables, such that the table that is the sum of the series is equal to the original table. Each table in the series has the same domain as the original table but can be expressed as a product of one- dimensional tables. Entries in tables are allowed to be any real number, i. e. they can be also negative numbers. The possibility of having...

Exploiting Tree Decomposition for Guiding Neighborhoods Exploration for VNS

Mathieu Fontaine, Samir Loudni, Patrice Boizumault (2013)

RAIRO - Operations Research - Recherche Opérationnelle

Tree decomposition introduced by Robertson and Seymour aims to decompose a problem into clusters constituting an acyclic graph. There are works exploiting tree decomposition for complete search methods. In this paper, we show how tree decomposition can be used to efficiently guide local search methods that use large neighborhoods like VNS. We propose DGVNS (Decomposition Guided VNS) which uses the graph of clusters in order to build neighborhood structures enabling better diversification and intensification....

Extraction of fuzzy logic rules from data by means of artificial neural networks

Martin Holeňa (2005)

Kybernetika

The extraction of logical rules from data has been, for nearly fifteen years, a key application of artificial neural networks in data mining. Although Boolean rules have been extracted in the majority of cases, also methods for the extraction of fuzzy logic rules have been studied increasingly often. In the paper, those methods are discussed within a five-dimensional classification scheme for neural-networks based rule extraction, and it is pointed out that all of them share the feature of being...

Extraction of fuzzy rules using deterministic annealing integrated with ε-insensitive learning

Robert Czabański (2006)

International Journal of Applied Mathematics and Computer Science

A new method of parameter estimation for an artificial neural network inference system based on a logical interpretation of fuzzy if-then rules (ANBLIR) is presented. The novelty of the learning algorithm consists in the application of a deterministic annealing method integrated with ε-insensitive learning. In order to decrease the computational burden of the learning procedure, a deterministic annealing method with a "freezing" phase and ε-insensitive learning by solving a system of linear inequalities...

Eye localization for face recognition

Paola Campadelli, Raffaella Lanzarotti, Giuseppe Lipori (2006)

RAIRO - Theoretical Informatics and Applications

We present a novel eye localization method which can be used in face recognition applications. It is based on two SVM classifiers which localize the eyes at different resolution levels exploiting the Haar wavelet representation of the images. We present an extensive analysis of its performance on images of very different public databases, showing very good results.

Currently displaying 21 – 36 of 36

Previous Page 2