Handle is an important property of fabrics. In this work we tried to predict the handles of some worsted fabrics by their physical properties using a backpropagation network. Also an unsupervised kohonen network was used for clustering the fabrics. Physical properties of fabrics were measured by universal test equipments and hand values of the fabrics were determined by a panel of judges consis...

In this paper, we propose a new model for two purposes: (1) discovering communities of users on social networks via topics with the temporal factor and (2) analyzing the changes in interested topics and users in communities in each period of time. This model, we use Kohonen network (SelfOrganizing Map) combining with the topic model. After discovering communities, results are shown on output la...

This paper explores the potential for utilising specialised hardware for the implementation of the Kohonen model and its derivative models. The adaptation periods of these algorithms is potentially protracted and computationally expensive; especially for the Adaptive Kohonen model in real-world, on-line applications. This paper analyses these models and highlights inherent parallelism. This ana...

Analysis of patterns of temporal variation in community dynamics was conducted by combining two unsupervised artificial neural networks, the Adaptive Resonance Theory (ART) and the Kohonen network. The field data used as input for training represented monthly changes in density and species richness in selected taxa of benthic macroinvertebrates collected in the Suyong River in Korea from Septem...

Social Network Analysis is an approach to analysing organisations focusing on relationships as the most important aspect. In this paper we discuss visualisation techniques for Social Network Analysis, including spring-embedding and simulated annealing techniques. We introduce a visualisation technique based on Kohonen neural networks, and also introduce social flow diagrams for demonstrating th...

A performance comparison of two self-organizing networks, the Kohonen Feature Map and the recently proposed Growing Cell Structures is made. For this purpose several performance criteria for self-organizing networks are proposed and motivated. The models are tested with three example problems of increasing difficulty. The Kohonen Feature Map demonstrates slightly superior results only for the s...

This paper presents a fuzzy system that recognizes learning styles and emotions using two different neural networks. The first neural network (a Kohonen neural network) recognizes the student cognitive style. The second neural network (a back-propagation neural network) was used to recognize the student emotion. Both neural networks are being part of a fuzzy system used into an intelligent tuto...