. Different authors have developed modifications of the Kohonen Self-Organizing Maps to solve known combinatorial optimization problems. In this paper a modification of the Kohonen Map is proposed to solve the detection of white inter-text spaces in a digitized plain text documents. The idea relies on the fact that line extraction problem has several features which match easily with Kohonen net...

We use a one-dimensional Kohonen network for detecting the angular position of an infrared beacon in front of an experimental autonomous vehicle. The inputs to the Kohonen network are the analog output signals from eight infrared detectors arranged along a semicircle on the front of the vehicle. By letting the network self-organise while a beacon is moved from one side to the other in front of ...

We develop an unsupervised “dual-network” connectionist model of category learning in which rules gradually emerge from a standard Kohonen network. The architecture is based on the interaction of a statistical-learning (Kohonen) network and a competitive-learning rule network. The rules that emerge in the rule network are weightings of individual features according to their importance for categ...

Kohonen self-organisation maps are a well know classification tool, commonly used in a wide variety of problems, but with limited applications in time series forecasting context. In this paper, we propose a forecasting method specifically designed for long-term trends prediction, with a double application of the Kohonen algorithm. We also consider practical issues for the use of the method.

Currently, there exist many research areas that produce large multivariable datasets that are difficult to visualize in order to extract useful information. Kohonen selforganizing maps have been used successfully in the visualization and analysis of multidimensional data. In this work, a projection technique that compresses multidimensional datasets into two dimensional space using growing self...

Kohonen self-organisation maps are a well know classification tool, commonly used in a wide variety of problems, but with limited applications in time series forecasting context. In this paper, we propose a forecasting method specifically designed for multi-dimensional long-term trends prediction, with a double application of the Kohonen algorithm. Practical applications of the method are also ...

in the science of operation research and decision theory, selection is the most important process. selection is a process that studies multiple qualitative and quantitative criteria, related to the science of management, which are mostly incompatible with each other. the multi criteria selection of a renewable energy portfolio is one of the main issues considered in multi criteria literature. i...

Background. A Kohonen topological map is an artificial intelligence system of the connectionist school (neural networks). The map learns the typical features of the subclasses in the learning set by means of a shortest Euclidean distance algorithm, after which selfadaptation of the neurons occurs. By its ability of selforganization and generalization, a Kohonen map is useful for pattern recogni...