The dramatic increase in geospatial data occasioned by developments in digital mapping, remote sensing, IT, and widespread generalization of Geographic Information Systems (GIS), emphasises the importance of exploring new approaches to spatial analysis ...

Granulation of information is a new way to describe the increased complexity of natural phenomena. The lack of clear borders in nature calls for a more efficient way to process such data. Land use both in general but also as perceived in satellite ...

Genetic algorithms (GA) have been found to provide global near optimal solutions in a wide range of complex problems. In this paper genetic algorithms have been used to deal with the complex problem of zone design. The zone design problem comprises a ...

A Feed forward multi-layered artificial neural network model is designed in this paper to estimate the maximum surface temperature and relative humidity needed for the genesis of severe thunderstorms over Calcutta (22° 32^′, 88° 20^′). The performance of ...

The evolution of digital technology has placed cartography in a dialog on questions concerning the new abilities, its form and prospective. The cartographic presentation in three dimensions has as a basic feature: the simulation with the “natural” ...

This paper introduces and formally defines a fuzzy rough object-oriented database (OODB) model based on a formal framework using an algebraic type system and formally defined constraints. This generalized model incorporates both rough set and fuzzy set ...

Spatial data mining refers to the extraction of knowledge, spatial relationships, or other interesting patterns not explicitly stored in spatial databases. The approaches usually followed in the analysis of geo-spatial data with the aim of knowledge ...

A new algorithm for generating a symmetric min-transitive opening of a similarity relation is proposed. Since min-transitive similarity relations are in one-to-one correspondence to hierarchical partition trees, our algorithm can be compared to certain ...

This research is concerned with a gradient descent training algorithm of a min-max network which we will refer to as the target network. Training makes use of a helper feed-forward network (FFN) to represent the performance function used in training the ...

In this paper, a new selective feedback fuzzy neural network (SFNN) based on interval type-2 fuzzy logic systems is introduced by partitioning input and output spaces and based upon which a new FLS filter is further studied. The experimental results ...