The paper presents some aspects regarding the use of pattern recognition techniques and neural networks for the activity evolution diagnostication and prediction by means of a set of indicators. Starting from the indicators set there is defined a measure on the patterns set, measure representing...

In this paper we present a modification of the strongly diluted Hopfield model in which the dilution scheme, instead of being random, is inspired on biological grounds. We also show that the resulting sparsely connected neural network shows striking features in terms of performance as an...

Morphological transformations are efficient methods for shape analysis and representation. In this paper two morphological shape descriptors are described for object feature representation. Neural networks are then employed for object recognition and classification. Various coding schemes and...

The use of n-tuple or weightless neural networks as pattern recognition devices is well known (Aleksander and Stonham, 1979). They have some significant advantages over the more common and biologically plausible networks, such as multi-layer perceptrons; for example, n-tuple networks have been...

An ANN (artificial neural network) approach was used to model the fuel consumption of wheat production. This study was conducted over 35,300 ha of irrigated and dry land wheat fields in Canterbury in the 2007–2008 harvest year. From an extensive data collection involving 40 farms, the total...

This editorial describes a special issue of Statistical Applications in Genetics and Molecular Biology that presents a full report on an international competition on mass spectrometry proteomic diagnosis, recently organised at the Leiden University Medical Centre in The Netherlands.

Purpose – The purpose of this paper is to examine two different approaches in the prediction of the economic recession periods in the US economy. Design/methodology/approach – A logit regression was applied and the prediction performance in two out-of-sample periods, 2007-2009 and 2010 was...

We study the applicability of the pattern recognition methodology "rough set data analysis" (RSDA) in the field of meta analysis. We give a summary of the mathematical and statistical background and then proceed to an application of the theory to a meta analysis of empirical studies dealing with...

We study connectivity of stones on a Go Board, including influence and heuristics-based soft connectivity and pattern- and search-based hard connectivity. Stone connectivity provides a Go program with an understanding of a fundamental aspect of board configurations. It is essential in positional...