Data Driven Modeling Using Spherical Self Organizing Feature Maps
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Data Driven Modeling Using Spherical Self Organizing Feature Maps
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Author : Archana Sangole
language : en
Publisher: Universal-Publishers
Release Date : 2006-04-28
Data Driven Modeling Using Spherical Self Organizing Feature Maps written by Archana Sangole and has been published by Universal-Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-04-28 with Technology & Engineering categories.
Researchers and data analysts are increasingly relying on graphical tools to assist them in modeling their data, generating their hypotheses, and gaining deeper insights on their experimentally acquired data. Recent advances in technology have made available more improved and novel modeling and analysis media that facilitate intuitive, task-driven exploratory analysis and manipulation of the displayed graphical representations. In order to utilize these emerging technologies researchers must be able to transform experimentally acquired data vectors into a visual form or secondary representation that has a simple structure and, is easily transferable into the media. As well, it is essential that it can be modified or manipulated within the display environment. This thesis presents a data-driven modeling technique that utilizes the basic learning strategy of an unsupervised clustering algorithm, called the self-organizing feature map, to adaptively learn topological associations inherent in the data and preserve them within the topology imposed by its predefined spherical lattice, thereby transforming the data into a 3D tessellated form. The tessellated graphical forms originate from a sphere thereby simplifying the process of computing its transformation parameters on re-orientation within an interactive, task-driven, graphical display medium. A variety of data sets including six sets of scattered 3D coordinate data, chaotic attractor data, the more commonly used Fisher s Iris flower data, medical numeric data, geographic and environmental data are used to illustrate the data-driven modeling and visualization mechanism. The modeling algorithm is first applied to scattered 3D coordinate data to understand the influence of the spherical topology on data organization. Two cases are examined, one in which the integrity of the spherical lattice is maintained during learning and, the second, in which the inter-node connections in the spherical lattice are adaptively changed during learning. In the analysis, scattered coordinate data of freeform objects with topology equivalent to a sphere and those whose topology is not equivalent to a sphere are used. Experiments demonstrate that it is possible to get reasonably good results with the degree of resemblance, determined by an average of the total normalized error measure, ranging from 6.2x10-5 1.1x10-3. The experimental analysis using scattered coordinate data facilitates an understanding of the algorithm and provides evidence of the topology-preserving capability of the spherical self-organizing feature map. The algorithm is later implemented using abstract, seemingly random, numeric data. Unlike in the case of 3D coordinate data, wherein the SOFM lattice is in the same coordinate frame (domain) as the input vectors, the numeric data is abstract. The criterion for deforming the spherical lattice is determined using mathematical and statistical functions as measures-of information that are tailored to reflect some aspect of meaningful, tangible, inter-vector relationships or associations embedded in the spatial data that reveal some physical aspect of the data. These measures are largely application-dependent and need to be defined by the data analyst or an expert. Interpretation of the resulting 3D tessellated graphical representation or form (glyph) is more complex and task dependent as compared to that of scattered coordinate data. Very simple measures are used in this analysis in order to facilitate discussion of the underlying mechanism to transform abstract numeric data into 3D graphical forms or glyphs. Several data sets are used in the analysis to illustrate how novel characteristics hidden in the data, and not easily apparent in the string of numbers, can be reflected via 3D graphical forms. The proposed data-driven modeling approach provides a viable mechanism to generate 3D tessellated representations of data that can be easily transferred to a graphical modeling and ana
Data Driven Modeling Using Spherical Self Organizing Feature Maps
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Author : Archana P Sangole
language : en
Publisher:
Release Date : 2003
Data Driven Modeling Using Spherical Self Organizing Feature Maps written by Archana P Sangole and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003 with Computer simulation categories.
Data Driven Modeling Using Spherical Self Organizing Feature Maps
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Author : Archana P Sangole
language : en
Publisher:
Release Date : 2003
Data Driven Modeling Using Spherical Self Organizing Feature Maps written by Archana P Sangole and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003 with Computer simulation categories.
Applications Of Self Organizing Maps
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Author : Magnus Johnsson
language : en
Publisher: BoD – Books on Demand
Release Date : 2012-11-21
Applications Of Self Organizing Maps written by Magnus Johnsson and has been published by BoD – Books on Demand this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-11-21 with Computers categories.
The self-organizing map, first described by the Finnish scientist Teuvo Kohonen, can by applied to a wide range of fields. This book is about such applications, i.e. how the original self-organizing map as well as variants and extensions of it can be applied in different fields. In fourteen chapters, a wide range of such applications is discussed. To name a few, these applications include the analysis of financial stability, the fault diagnosis of plants, the creation of well-composed heterogeneous teams and the application of the self-organizing map to the atmospheric sciences.
Kohonen Maps
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Author : E. Oja
language : en
Publisher: Elsevier
Release Date : 1999-07-02
Kohonen Maps written by E. Oja and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 1999-07-02 with Computers categories.
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 SOM to clustering, classification, probabilistic models, and energy functions. Many applications of the SOM are given, with data mining and exploratory data analysis the central topic, applied to large databases of financial data, medical data, free-form text documents, digital images, speech, and process measurements. Biological models related to the SOM are also discussed.
Advances In Self Organizing Maps
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Author : Pablo A. Estévez
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-14
Advances In Self Organizing Maps written by Pablo A. Estévez and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-14 with Technology & Engineering categories.
Self-organizing maps (SOMs) were developed by Teuvo Kohonen in the early eighties. Since then more than 10,000 works have been based on SOMs. SOMs are unsupervised neural networks useful for clustering and visualization purposes. Many SOM applications have been developed in engineering and science, and other fields. This book contains refereed papers presented at the 9th Workshop on Self-Organizing Maps (WSOM 2012) held at the Universidad de Chile, Santiago, Chile, on December 12-14, 2012. The workshop brought together researchers and practitioners in the field of self-organizing systems. Among the book chapters there are excellent examples of the use of SOMs 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 SOMs as well as Learning Vector Quantization (LVQ) methods.
Archaeology Research Trends
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Author : Alex R. Suárez
language : en
Publisher:
Release Date : 2008
Archaeology Research Trends written by Alex R. Suárez and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008 with Social Science categories.
Archaeology studies human cultures through the recovery, documentation, analysis and interpretation of material remains and environmental data, including architecture, artefacts, features, biofacts, and landscapes. Because archaeology's aim is to understand mankind, it is a humanistic endeavour. The goals of archaeology vary, and there is debate as to what its aims and responsibilities are. Some goals include the documentation and explanation of the origins and development of human cultures, understanding culture history, chronicling cultural evolution, and studying human behaviour and ecology, for both prehistoric and historic societies. This advanced book presents important research in the field.
Knowledge Based And Intelligent Information And Engineering Systems
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Author : Rossitza Setchi
language : en
Publisher: Springer
Release Date : 2010-09-08
Knowledge Based And Intelligent Information And Engineering Systems written by Rossitza Setchi and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-09-08 with Computers categories.
th The 14 International Conference on Knowledge-Based and Intelligent Information and Engineering Systems was held during September 8–10, 2010 in Cardiff, UK. The conference was organized by the School of Engineering at Cardiff University, UK and KES International. KES2010 provided an international scientific forum for the presentation of the - sults of high-quality research on a broad range of intelligent systems topics. The c- ference attracted over 360 submissions from 42 countries and 6 continents: Argentina, Australia, Belgium, Brazil, Bulgaria, Canada, Chile, China, Croatia, Czech Republic, Denmark, Finland, France, Germany, Greece, Hong Kong ROC, Hungary, India, Iran, Ireland, Israel, Italy, Japan, Korea, Malaysia, Mexico, The Netherlands, New Zealand, Pakistan, Poland, Romania, Singapore, Slovenia, Spain, Sweden, Syria, Taiwan, - nisia, Turkey, UK, USA and Vietnam. The conference consisted of 6 keynote talks, 11 general tracks and 29 invited s- sions and workshops, on the applications and theory of intelligent systems and related areas. The distinguished keynote speakers were Christopher Bishop, UK, Nikola - sabov, New Zealand, Saeid Nahavandi, Australia, Tetsuo Sawaragi, Japan, Yuzuru Tanaka, Japan and Roger Whitaker, UK. Over 240 oral and poster presentations provided excellent opportunities for the presentation of interesting new research results and discussion about them, leading to knowledge transfer and generation of new ideas. Extended versions of selected papers were considered for publication in the Int- national Journal of Knowledge-Based and Intelligent Engineering Systems, Engine- ing Applications of Artificial Intelligence, Journal of Intelligent Manufacturing, and Neural Computing and Applications.
Multimedia Database Retrieval
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Author : Paisarn Muneesawang
language : en
Publisher: Springer
Release Date : 2014-10-25
Multimedia Database Retrieval written by Paisarn Muneesawang and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-10-25 with Computers categories.
This book explores multimedia applications that emerged from computer vision and machine learning technologies. These state-of-the-art applications include MPEG-7, interactive multimedia retrieval, multimodal fusion, annotation, and database re-ranking. The application-oriented approach maximizes reader understanding of this complex field. Established researchers explain the latest developments in multimedia database technology and offer a glimpse of future technologies. The authors emphasize the crucial role of innovation, inspiring users to develop new applications in multimedia technologies such as mobile media, large scale image and video databases, news video and film, forensic image databases and gesture databases. With a strong focus on industrial applications along with an overview of research topics, Multimedia Database Retrieval: Technology and Applications is an indispensable guide for computer scientists, engineers and practitioners involved in the development and use of multimedia systems. It also serves as a secondary text or reference for advanced-level students interested in multimedia technologies.
Advances In Artificial Intelligence Iberamia 2002
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Author : Francisco J. Garijo
language : en
Publisher: Springer Science & Business Media
Release Date : 2002-10-30
Advances In Artificial Intelligence Iberamia 2002 written by Francisco J. Garijo and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2002-10-30 with Computers categories.
This book constitutes the refereed proceedings of the 8th Ibero-American Conference on Artificial Intelligence, IBERAMIA 2002, held in Seville, Spain, in November 2002. The 97 revised full papers presented were carefully reviewed and selected from a total of 345 submissions. The papers are organized in topical sections on knowledge representation and reasoning, machine learning, uncertainty and fuzzy systems, genetic algorithms, neural nets, distributed artificial intelligence and multi-agent systems, natural language processing, intelligent tutoring systems, control and real time, robotics, and computer vision.