We describe the MusicMiner system for organizing large collections of music with databionic mining techniques. Visualization based on perceptually motivated audio features and Emergent Self-Organizing Maps enables the unsupervised discovery of timbrally consistent clusters that may or may not correspond to musical genres and artists. We demonstrate the visualization capabilities of the U-Map. A...

Role of self-organizing maps in visualization and analysis of software measures is presented and discussed in this paper. We reveal how self-organizing maps can create a user-friendly and interactive visualization tool that helps software designer to inspect various alternatives and get a thorough insight into the structure of the clusters of the software modules and related metrics. We show ho...

Abstract In this study, we present self-organizing maps and discuss their role in the analysis and visualization of software modules in the space of software measures. We reveal how self-organizing maps create a user-friendly and interactive visualization tool that helps user/software designer inspect various alternatives and get a thorough insight into the structure of the clusters of the soft...

Collision avoidance for a visuo-motor system in unstructured and cluttered environment is described. The achievement of collision avoidance is based on a simplified path planning system and motion control performed by self-organizing maps. The self-organizing maps are learned to determine joint angles of a redundant manipulator. Since the learning algorithm promises to make the manipulator reac...

A dynamically reconfigurable hardware accelerator for self-organizing feature maps is presented. The system is based on the universal rapid prototyping system RAPTOR2000 that has been developed by the authors. The modular prototyping system is based on XILINX FPGAs and is capable of emulating hardware implementations with a complexity of more than 24 million system gates. RAPTOR2000 is linked t...

In this paper we present an approach to organize and classify e-mails using self-organizing maps. The aim is on the one hand to provide an intuitive visual profile of the considered mailing lists and on the other hand to offer an intuitive navigation tool, were similar e-mails are located close to each other, so that the user can scan easily for e-mails similar in content. Furthermore, each gro...

Steel consumption is a critical factor affecting pricing decisions and a key element to achieve sustainable industrial development. Forecasting future trends of steel consumption based on analysis of nonlinear patterns using artificial intelligence (AI) techniques is the main purpose of this paper. Because there are several features affecting target variable which make the analysis of relations...

Using soft computing methods, the authors collect and process relevant user-generated information from the web. Through the use of self-organizing maps, fuzzy cognitive maps are constructed. The fuzzy cognitive map is a generated representation of the emergent web semantics of the dataset. In the next step, the fuzzy cognitive maps are enriched with related lexical content and stored in a graph...

In the framework of SOM methodology for process and system analysis, we suggest a method for identifying regions in the SOM visualization space corresponding to different conditions of a monitored process by means of a fuzzy rule system, as a way of incorporating expert knowledge to this methodology.

Self-organizing maps have been used extensively for condition-based maintenance, where quantization errors of test data referring to the self-organizing maps of healthy training data have been used as features. Researchers have used minimum quantization error as a health indicator, which is sensitive to noise in the training data. Some other researchers have used the average of the quantization...