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Neural networks (Computer science) --- Self-organizing maps --- Algorithms, Kohonen --- Kohonen algorithms --- Kohonen maps --- Kohonen's maps --- Maps, Kohonen --- Maps, Self-organizing --- SOMs (Self-organizing maps) --- Self-organizing systems

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The Self-Organizing Map, or Kohonen Map, is one of the most widely used neural network algorithms, with thousands of applications covered in the literature. It was one of the strong underlying factors in the popularity of neural networks starting in the early 80's. Currently this method has been included in a large number of commercial and public domain software packages. In this book, top experts on the SOM method take a look at the state of the art and the future of this computing paradigm. The 30 chapters of this book cover the current status of SOM theory, such as connections of S

Artificial intelligence. Robotics. Simulation. Graphics --- Neural networks (Computer science). --- Self-organizing maps. --- Neural networks (Computer science) --- Algorithms, Kohonen --- Kohonen algorithms --- Kohonen maps --- Kohonen's maps --- Maps, Kohonen --- Maps, Self-organizing --- SOMs (Self-organizing maps) --- Self-organizing systems --- Artificial neural networks --- Nets, Neural (Computer science) --- Networks, Neural (Computer science) --- Neural nets (Computer science) --- Artificial intelligence --- Natural computation --- Soft computing

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The book collects the scientific contributions presented at the 10th Workshop on Self-Organizing Maps (WSOM 2014) held at the University of Applied Sciences Mittweida, Mittweida (Germany, Saxony), on July 2–4, 2014. Starting with the first WSOM-workshop 1997 in Helsinki this workshop focuses on newest results in the field of supervised and unsupervised vector quantization like self-organizing maps for data mining and data classification.   This 10th WSOM brought together more than 50 researchers, experts and practitioners in the beautiful small town Mittweida in Saxony (Germany) nearby the mountains Erzgebirge to discuss new developments in the field of unsupervised self-organizing vector quantization systems and learning vector quantization approaches for classification. The book contains the accepted papers of the workshop after a careful review process as well as summaries of the invited talks.   Among these book chapters there are excellent examples of the use of self-organizing maps in agriculture, computer science, data visualization, health systems, economics, engineering, social sciences, text and image analysis, and time series analysis. Other chapters present the latest theoretical work on self-organizing maps as well as learning vector quantization methods, such as relating those methods to classical statistical decision methods. All the contribution demonstrate that vector quantization methods cover a large range of application areas including data visualization of high-dimensional complex data, advanced decision making and classification or data clustering and data compression.

Engineering. --- Artificial intelligence. --- Computational intelligence. --- Computational Intelligence. --- Artificial Intelligence (incl. Robotics). --- Intelligence, Computational --- Artificial intelligence --- Soft computing --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Electronic data processing --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Construction --- Industrial arts --- Technology --- Neural networks (Computer science) --- Self-organizing maps --- Algorithms, Kohonen --- Kohonen algorithms --- Kohonen maps --- Kohonen's maps --- Maps, Kohonen --- Maps, Self-organizing --- SOMs (Self-organizing maps) --- Artificial Intelligence.

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This book contains the articles from the international conference 11th Workshop on Self-Organizing Maps 2016 (WSOM 2016), held at Rice University in Houston, Texas, 6-8 January 2016. WSOM is a biennial international conference series starting with WSOM'97 in Helsinki, Finland, under the guidance and direction of Professor Tuevo Kohonen (Emeritus Professor, Academy of Finland). WSOM brings together the state-of-the-art theory and applications in Competitive Learning Neural Networks: SOMs, LVQs and related paradigms of unsupervised and supervised vector quantization. The current proceedings present the expert body of knowledge of 93 authors from 15 countries in 31 peer reviewed contributions. It includes papers and abstracts from the WSOM 2016 invited speakers representing leading researchers in the theory and real-world applications of Self-Organizing Maps and Learning Vector Quantization: Professor Marie Cottrell (Universite Paris 1 Pantheon Sorbonne, France), Professor Pablo Estevez (University of Chile and Millennium Instituteof Astrophysics, Chile), and Professor Risto Miikkulainen (University of Texas at Austin, USA). The book comprises a diverse set of theoretical works on Self-Organizing Maps, Neural Gas, Learning Vector Quantization and related topics, and an excellent variety of applications to data visualization, clustering, classification, language processing, robotic control, planning, and to the analysis of astronomical data, brain images, clinical data, time series, and agricultural data.

Computer Science --- Engineering & Applied Sciences --- Neural networks (Computer science) --- Self-organizing maps --- Self-organizing systems --- Algorithms, Kohonen --- Kohonen algorithms --- Kohonen maps --- Kohonen's maps --- Maps, Kohonen --- Maps, Self-organizing --- SOMs (Self-organizing maps) --- Engineering. --- Artificial intelligence. --- Computational intelligence. --- Computational Intelligence. --- Artificial Intelligence (incl. Robotics). --- Intelligence, Computational --- Artificial intelligence --- Soft computing --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Electronic data processing --- Logic machines --- Machine theory --- Simulation methods --- Fifth generation computers --- Neural computers --- Construction --- Industrial arts --- Technology --- Artificial Intelligence.

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Self-organizing maps (SOM) have proven to be of significant economic value in the areas of finance, economic and marketing applications. As a result, this area is rapidly becoming a non-academic technology. This book looks at near state-of-the-art SOM applications in the above areas, and is a multi-authored volume, edited by Guido Deboeck, a leading exponent in the use of computational methods in financial and economic forecasting, and by the originator of SOM, Teuvo Kohonen. The book contains chapters on applications of unsupervised neural networks using Kohonen's self-organizing map approach.

Finance --- Neural networks (Computer science) --- Self-organizing maps --- Decision making --- Data processing --- Self-organizing maps. --- Artificial intelligence. Robotics. Simulation. Graphics --- Neural networks (Computer science). --- Data processing. --- Economics, Mathematical . --- Atoms. --- Physics. --- Finance. --- Quantitative Finance. --- Atomic, Molecular, Optical and Plasma Physics. --- Finance, general. --- Funding --- Funds --- Economics --- Currency question --- Natural philosophy --- Philosophy, Natural --- Physical sciences --- Dynamics --- Chemistry, Physical and theoretical --- Matter --- Stereochemistry --- Mathematical economics --- Econometrics --- Mathematics --- Constitution --- Methodology --- Artificial neural networks --- Nets, Neural (Computer science) --- Networks, Neural (Computer science) --- Neural nets (Computer science) --- Artificial intelligence --- Natural computation --- Soft computing --- Algorithms, Kohonen --- Kohonen algorithms --- Kohonen maps --- Kohonen's maps --- Maps, Kohonen --- Maps, Self-organizing --- SOMs (Self-organizing maps) --- Self-organizing systems --- Finance - Decision making - Data processing