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Dissertations / Theses on the topic 'Growing Self Organizing Map'

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Published: 3 June 2025
Last updated: 31 July 2025

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1

Malondkar, Ameya Mohan. "Extending the Growing Hierarchical Self Organizing Maps for a Large Mixed-Attribute Dataset Using Spark MapReduce." Thesis, Université d'Ottawa / University of Ottawa, 2015. http://hdl.handle.net/10393/33385.

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In this thesis work, we propose a Map-Reduce variant of the Growing Hierarchical Self Organizing Map (GHSOM) called MR-GHSOM, which is capable of handling mixed attribute datasets of massive size. The Self Organizing Map (SOM) has proved to be a useful unsupervised data analysis algorithm. It projects a high dimensional data onto a lower dimensional grid of neurons. However, the SOM has some limitations owing to its static structure and the incapability to mirror the hierarchical relations in the data. The GHSOM overcomes these shortcomings of the SOM by providing a dynamic structure that adap
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Orts-Escolano, Sergio. "A three-dimensional representation method for noisy point clouds based on growing self-organizing maps accelerated on GPUs." Doctoral thesis, Universidad de Alicante, 2013. http://hdl.handle.net/10045/36484.

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The research described in this thesis was motivated by the need of a robust model capable of representing 3D data obtained with 3D sensors, which are inherently noisy. In addition, time constraints have to be considered as these sensors are capable of providing a 3D data stream in real time. This thesis proposed the use of Self-Organizing Maps (SOMs) as a 3D representation model. In particular, we proposed the use of the Growing Neural Gas (GNG) network, which has been successfully used for clustering, pattern recognition and topology representation of multi-dimensional data. Until now, Self-O
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Liu, Yonggang. "Patterns and dynamics of ocean circulation variability on the West Florida shelf." [Tampa, Fla] : University of South Florida, 2006. http://purl.fcla.edu/usf/dc/et/SFE0001413.

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Farshad, Tabrizi Seyed Ramin. "The Probabilistic Supervised Self-Organizing Map, PSSOM." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1998. http://www.collectionscanada.ca/obj/s4/f2/dsk2/ftp01/MQ31828.pdf.

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Schwardt, Martin. "Lösung ausgewählter Routenplanungsprobleme mit Hilfe der self-organizing map." [S.l.] : [s.n.], 2005. http://deposit.ddb.de/cgi-bin/dokserv?idn=975255126.

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Pourkia, Javid. "A SELF-ORGANIZING MAP APPROACH FOR HOSPITAL DATA ANALYSIS." OpenSIUC, 2014. https://opensiuc.lib.siu.edu/theses/1553.

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In this work, we utilize Self Organized Maps (SOM) to cluster and classify hospital related data with large dimensions, provided by Medicare website. These data have published every year and it includes numerous measures for each hospital in the nationwide. It might be possible to unearth some correlations in health-care industry by being able to interpreting this dataset, for example by examining the relations between data of immunizations department to readmission records and hospital expenses. It is not feasible to make any sense from these measures altogether using traditional methods (2D
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Choe, Yoonsuck. "Perceptual grouping in a self-organizing map of spiking neurons." Access restricted to users with UT Austin EID Full text (PDF) from UMI/Dissertation Abstracts International, 2001. http://wwwlib.umi.com/cr/utexas/fullcit?p3025202.

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8

Wang, Dali. "Adaptive Double Self-Organizing Map for Clustering Gene Expression Data." Fogler Library, University of Maine, 2003. http://www.library.umaine.edu/theses/pdf/WangD2003.pdf.

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9

Bui, Michael. "Path finding on a spherical self-organizing map using distance transformations." Thesis, The University of Sydney, 2008. http://hdl.handle.net/2123/9290.

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Spatialization methods create visualizations that allow users to analyze high-dimensional data in an intuitive manner and facilitates the extraction of meaningful information. Just as geographic maps are simpli ed representations of geographic spaces, these visualizations are esssentially maps of abstract data spaces that are created through dimensionality reduction. While we are familiar with geographic maps for path planning/ nding applications, research into using maps of high-dimensional spaces for such purposes has been largely ignored. However, literature has shown that it is possible t
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Tervonen, J. (Jaakko). "Exploring behaviour patterns with self-organizing map for personalised mental stress detection." Master's thesis, University of Oulu, 2019. http://jultika.oulu.fi/Record/nbnfioulu-201904131491.

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Abstract. Stress is an important health problem and the cause for many illnesses and working days lost. It is often measured with different questionnaires that capture only the current stress levels and may come in too late for early prevention. They are also prone to subjective inaccuracies since the feeling of stress, and the physiological response to it, have been found to be individual. Real-time stress detectors, trained on biosignals like heart rate variability, exist but majority of them employ supervised learning which requires collecting a large amount of labelled data from each syste
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Mewes, Daniel, and Ch Jacobi. "Analyzing Arctic surface temperatures with Self Organizing-Maps: Influence of the maps size." Universität Leipzig, 2018. https://ul.qucosa.de/id/qucosa%3A31794.

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We use ERA-Interim reanalysis data of 2 meter temperature to perform a pattern analysis of the Arctic temperatures exploiting an artificial neural network called Self Organizing-Map (SOM). The SOM method is used as a cluster analysis tool where the number of clusters has to be specified by the user. The different sized SOMs are analyzed in terms of how the size changes the representation of specific features. The results confirm that the larger the SOM is chosen the larger will be the root mean square error (RMSE) for the given SOM, which is followed by the fact that a larger number of pattern
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12

Wandeto, John Mwangi. "Self-organizing map quantization error approach for detecting temporal variations in image sets." Thesis, Strasbourg, 2018. http://www.theses.fr/2018STRAD025/document.

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Une nouvelle approche du traitement de l'image, appelée SOM-QE, qui exploite quantization error (QE) des self-organizing maps (SOM) est proposée dans cette thèse. Les SOM produisent des représentations discrètes de faible dimension des données d'entrée de haute dimension. QE est déterminée à partir des résultats du processus d'apprentissage non supervisé du SOM et des données d'entrée. SOM-QE d'une série chronologique d'images peut être utilisé comme indicateur de changements dans la série chronologique. Pour configurer SOM, on détermine la taille de la carte, la distance du voisinage, le ryth
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HUANG, WEI LING, and 黃偉綾. "Development of an Ant-Based Growing Self-Organizing Map Neural Network." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/18030470427332588763.

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碩士<br>華梵大學<br>工業工程與經營資訊學系碩士班<br>96<br>Kohonen’s Self-Organizing Maps network (SOM) has been regarded as an effective analysis of data mining tools. The principle of the conventional SOM to determine the best matching unit (BMU) relies on the distance between the input vector and the weight vector of each topological neuron. To improve the Ant-Based Self-Organizing Map algorithm (ABSOM), this research proposes an Ant-Based Growing Self-Organizing Map (AGSOM) algorithm, which adopts the exploitation and exploration rules of the Ant Colony Optimization (ACO) to determine the BMU. In AGSOM, the ro
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Jheng, Zong-Hao, and 鄭宗豪. "Process Monitor for Autocorrelated Data by Growing Hierarchical Self-Organizing Map." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/5y9m7e.

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碩士<br>國立臺北科技大學<br>商業自動化與管理研究所<br>96<br>Generally speaking, Managers address themselves to monitor and adjust process in order to effectively enhance the quality of product. Statistical Process Control (SPC) and Engineer Process Control (EPC) have been widely applied. When the data is without attribution of self-correlated, integrating SPC and EPC can effectively discriminate the assignable causes and remove them. However, when the data is with attribution of self-correlated, there is a problem that integration of SPC and EPC may inform a false alarm. In this paper, the concept of clustering is
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Tai, Wei-Shen, and 戴偉勝. "A Growing Self-Organizing Map for Visualization of Multivariate Mixed-Type Data." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/55926465515801425185.

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博士<br>國立雲林科技大學<br>資訊管理系博士班<br>100<br>Nowadays, abundant multivariate mixed-type data including numeric as well as categorical attributes are ubiquitous in a variety of applications. Therefore, processing and analyzing such mixed-type data has become an important issue in data mining field. Via visualization models, one is able to understand and analyze those relationships between complicated data more effortlessly. Self-Organizing Map (SOM) possesses an effective visualization capability for presenting the characteristics of high-dimensional data on a low-dimensional map. One can efficiently e
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Tsui, I.-Fong, and 崔怡楓. "Variability analysis of Kuroshio intrusion around Taiwan using growing hierarchical self-organizing map." Thesis, 2013. http://ndltd.ncl.edu.tw/handle/35640387688006224708.

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Rizki, Muhammad, and Muhammad Rizki. "Integration of Growing Self-Organizing Map and Bee Colony Optimization Algorithm for Group Technology." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/8fxx49.

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碩士<br>國立臺灣科技大學<br>工業管理系<br>102<br>This research proposes two-stage method, growing self-organizing map (GSOM) algorithm and bee colony optimization (BCO) based self-organizing map (BSOSOM), to improve SOM performance. In the first stage, GSOM is used to determine the SOM topology and then followed by BCOSOM to fine tune the SOM weights. The proposed BCOSOM algorithm is compared with other algorithms, PSO, BCO, SOM, PSOSOM, SOM+PSO, and SOM+BCO, using four benchmark data sets, Iris, Glass, Wine, and Vowel. The computational result indicates that BCOSOM algorithm is able to find a better solutio
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Da-ChengYu and 余大成. "Indexing and Retrieval of Human Motion Data Based on a Growing Self-Organizing Map." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/30130993651582152483.

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碩士<br>國立成功大學<br>工程科學系<br>102<br>With low-cost depth cameras are released recently, motion data containing 3D coordinates of skeleton joints during a time period can be directly captured. Nevertheless, analyzing the motion data is usually a challenging problem and requires huge computation costs because of the high-dimensionality. Among several alternatives, the self-organizing map (SOM) is verified to be an effective technique to handle such motion data. Specifically, a captured motion sequence can be easily and precisely mapped to form an indexed motion string through the use of a trained SOM
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Khasanah, Annisa Uswatun, and Annisa Uswatun Khasanah. "Integration of Growing Self-Organizing Map and Particle Swarm Optimization Algorithm for Group Technology." Thesis, 2013. http://ndltd.ncl.edu.tw/handle/55306139622036638320.

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碩士<br>國立臺灣科技大學<br>工業管理系<br>101<br>This study attempts to employ Growing Self-Organizing Map (GSOM) algorithm and Particle Swarm Optimization (PSO)-based Self Organizing Map (PSOSOM) to improve the performance of SOM. The proposed GSOM+PSOSOM approach for SOM is consisted of two stages. In the first stage, GSOM is used to determine the SOM topology and then followed by PSOSOM in the second stage to fine tune the SOM weights. The proposed PSOSOM algorithm is compared with other two algorithms and also compare to CGASOM from the previous study using four benchmark datasets, Iris, Wine, Vowel, and
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Wang, Chih-Fehn, and 王志峯. "The Development and Application of Integration of Growing Self-Organizing Map and Genetic Algorithm." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/2kzvcr.

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碩士<br>國立臺北科技大學<br>工業工程與管理研究所<br>96<br>In recent years, clustering analysis has been widely applied in may areas, like engineering, management, and bioscience. The purpose is to segment the individuals with the same characteristics in the population into the same group. Thus, those belong to the same group are homogenous and have the same characteristics. On the hand, those belong to different groups are heterogonous and have different characteristics. Therefore, this study attempts to use Growing Self-Organizing Map (GSOM) with integration of Genetic Algorithm (GA) to accelerate searching glob
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Li, Wei-Ming, and 李偉銘. "A corporate financial crisis forecasting model using growing hierarchical self-organizing map and trajectory analysis." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/2xp9ar.

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碩士<br>國立臺北科技大學<br>經營管理系碩士班<br>100<br>In the field of forecasting corporate financial crisis, the univariate model、the discriminant analysis、the logistic regression and the neural networks were used to build forecasting models. Many literatures showed that these models perform better in short term forecasting, however, their accuracy rate sharply decline in long term forecasting. As a result, growing hierarchical self-organizing map and trajectory analysis are adopted in our research to overcome this drawback. Two hundred and twenty two companies, including 111 financial crisis companies and 11
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Tangsripairoj, Songsri. "A growing hierarchical self-organizing map with mining association rules for software repository organization and visualization." 2004. http://digital.library.okstate.edu/etd/umi-okstate-1123.pdf.

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Shu-Yuan, Hsiao, and 蕭淑媛. "An Integration Framework of Growing Hierarchical Self-Organizing Map and Case-based reasoning based on UML-A case study on Mr. Y.C. Wang’s Knowledge Maps." Thesis, 2006. http://ndltd.ncl.edu.tw/handle/95219157677333770188.

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碩士<br>長庚大學<br>企業管理研究所<br>94<br>The collection and application of corporate leaders’ knowledge has long been a major management issue. With the development of Internet and Information Technology, the developed Information Technology still doesn’t satisfy the user’s requirement in gathering the corporate leaders’ tacit knowledge. So this research builds a useful Case-base reasoning (CBR) system to assist decision makers in finding a past case similar to the new problems, and use that case to suggest a solution to the current problems, evaluate the proposed solution and update the system by learn
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Kit, Dmitry Mark. "Change detection models for mobile cameras." Thesis, 2012. http://hdl.handle.net/2152/ETD-UT-2012-05-5127.

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Change detection is an ability that allows intelligent agents to react to unexpected situations. This mechanism is fundamental in providing more autonomy to robots. It has been used in many different fields including quality control and network intrusion. In the visual domain, however, most research has been confined to stationary cameras and only recently have researchers started to shift to mobile cameras. \ We propose a general framework for building internal spatial models of the visual experiences. These models are used to retrieve expectations about visual inputs which can be
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Pereira, Silvério Matos. "Anomaly detection in mobile networks." Master's thesis, 2021. http://hdl.handle.net/10773/31374.

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Big data has become an increasingly important topic in recent years, with new sources of data comes the need to be aware of the trade-off it requires, necessitating great care in both choice and implementation of algorithms, as well as how to adapt existing algorithms to handle this new setting. At the same time, the interpretability and understanding of a small to medium number of features is still key in many areas where understanding the data is paramount. In this thesis we show how we can tackle both these issues with the aid of self-organizing algorithms. Two objectives were achie
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游鴻志. "Evolutionary Self-Organizing Map." Thesis, 1997. http://ndltd.ncl.edu.tw/handle/31927797953001438650.

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碩士<br>中原大學<br>資訊工程學系<br>85<br>Since the concept of neural network was introduced, there are many neural network models developed and used broadly in different research areas. In 1973, Kohonen proposes a new generation of neural network models, called Self-Organizing Map (SOM). The SOM algorithm adds one kinds of fixed neighborhood relations among neurons into regular neural nets and learns new patterns under such neighborhood constraints. 　　Although SOM has been proven to be effective in many applications, the fixedness of its neighborhood relations bring many inconveniences. This dissertation
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"Soft self-organizing map." Chinese University of Hong Kong, 1995. http://library.cuhk.edu.hk/record=b5888572.

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by John Pui-fai Sum.<br>Thesis (M.Phil.)--Chinese University of Hong Kong, 1995.<br>Includes bibliographical references (leaves 99-104).<br>Chapter 1 --- Introduction --- p.1<br>Chapter 1.1 --- Motivation --- p.1<br>Chapter 1.2 --- Idea of SSOM --- p.3<br>Chapter 1.3 --- Other Approaches --- p.3<br>Chapter 1.4 --- Contribution of the Thesis --- p.4<br>Chapter 1.5 --- Outline of Thesis --- p.5<br>Chapter 2 --- Self-Organizing Map --- p.7<br>Chapter 2.1 --- Introduction --- p.7<br>Chapter 2.2 --- Algorithm of SOM --- p.8<br>Chapter 2.3 --- Illustrative Example --- p.10<br>Chapter 2.4 -
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Cheng, Wei-Chen, and 鄭為正. "Distance Invariant Self-organizing Map." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/33410109389825158018.

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博士<br>臺灣大學<br>資訊工程學研究所<br>98<br>This dissertation presents a distance invariant manifold that preserves neighboring relationships among data patterns. Since all input patterns have their corresponding cells in the manifold space, the neighboring cells of the input pattern resembles that of the output patterns. The manifold is invariant under the translation, rotation and scale of the pattern coordinates. And the neighboring relationships among cells are adjusted and improved in each iteration according to the algorithm of reduction of the distance preservation energy. This dissertation also ex
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Hui-Ling, HSU, and 許惠玲. "Semantic Indexing using Self-Organizing Map." Thesis, 2001. http://ndltd.ncl.edu.tw/handle/24872588529247968441.

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碩士<br>國立臺灣大學<br>資訊工程學研究所<br>89<br>The information in literary works is rich. The task to read between the lines is challenging even for the most sophisticated system such as human brains. The main idea of this paper is to illustrate the design of a corpus-based method to find semantic structures in the complete works of Mark Twain (Samuel L. Clemens, 1835-1910), who was famous for his extraordinary sense of humor as well as social concern. Self-organizing Map (SOM) is applied to investigate the relations of vocabulary within the context of Mark Twain’s works. SOM make words cluster according
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Kuo, Kuan-hui, and 郭冠輝. "Application of Using Self-Organizing Feature Map in Concept Map." Thesis, 2004. http://ndltd.ncl.edu.tw/handle/68288164747667026745.

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碩士<br>國立臺南大學<br>資訊教育研究所教學碩士班<br>92<br>To achieve the learning objectives, tests are often used to measure the achievements of the learners in traditional way of teaching and learning. The result of testing not only provides the information about what learners have achieved but also identify learners’ weaknesses. A good test puts emphasis on exploring learners’ learning process in order to go into the cognitive behavior of the learners and to evaluate what learners have achieved. The Self-Organizing Feature Map of neural network is applied to integrating professionals’ and teachers’ differe
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Chen, De-Hua, and 陳德華. "Self-Organizing Map Networks for Symbolic Data." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/71732493029297668562.

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博士<br>中原大學<br>應用數學研究所<br>97<br>Abstract The Kohonen’s self-organizing map (SOM) is a competitive learning neural network that uses a neighborhood lateral interaction function to discover the topological structure hidden in the data set. It is an unsupervised approach. In general, the SOM neural network is constructed as a learning algorithm for numeric (vector) data. However, except these numeric data, there are many other data types such as symbolic data. The SOM algorithm cannot treat the symbolic data. In this dissertation we are interested in considering a modified SOM for symbolic data. T
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Lo, Yung-Ho, and 羅永和. "Chinese Document Clustering Using Self-Organizing Map." Thesis, 2004. http://ndltd.ncl.edu.tw/handle/97883278971622717173.

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碩士<br>國立高雄第一科技大學<br>資訊管理所<br>92<br>The 21st centenary is an age of information explosion. The continuous growth in the size and use of the Internet is creating difficulties in the search for information. Currently, the problem which the users encountered, are not lack of information but too much information. There is a need for automatic procedures that allow users to retrieve the information from the rich information sources. An effective algorithm to organize the structure of information and assist user to search information is therefore particularly important. As well known Category map de
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Li, Dong-Lin, and 李東霖. "Adaptive Self-Organizing Map and Its Applications." Thesis, 2006. http://ndltd.ncl.edu.tw/handle/25233280500026750414.

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碩士<br>國立中興大學<br>電機工程學系所<br>94<br>Self-organizing neural network is one of the methods frequently used in data clustering. In this thesis, we present a new method to improve the self-organizing map algorithm. Instead of the 2-D neighborhood topology in the conventional self-organizing map, a 3-D 6-neighbor topology is adopted in our approach. To avoid the dead (non-functional) neurons and to represent the training data more effectively, the number of neurons and the links between the neurons will be adjusted automatically during the process of the competitive learning by using a self-constructi
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Ke, Kuo-Lung, and 柯國隆. "Research on Topic Oriented Self-organizing Map." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/36641514148320184803.

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碩士<br>國立高雄大學<br>資訊管理學系碩士班<br>98<br>Text document clustering is a basic operation of text processing and is widely applied in data visualization, theme identification, text summarization, hierarchy generation, etc. However, it will be inconvenient for users to find a document after clustering without proper labeling of topics. Moreover, there exist hierarchical relationships between document clusters. In this work, we will propose an adaptive self-organizing map model, namely the topic-oriented self-organizing map (TOSOM), that can adaptively expand the map laterally and hierarchically accordin
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Lin, Chung-Fu, and 林長富. "Fractal Image Compression using Self-Organizing Map." Thesis, 2006. http://ndltd.ncl.edu.tw/handle/50071198199820242247.

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碩士<br>義守大學<br>資訊工程學系碩士班<br>94<br>Fractal Image Compression possesses the advantages of high compression ratio, low loss ratio, and fast decompression process. The use of exhaustive search in the encoding process results in a long encoding time. However, the encoding time can be reduced with a limiting searching space. Searching space can be limited to a certain cluster through clustering the domain pool to effectively shorten the comparison time and achieve the goal of reducing encoding time. In this paper, the clustering of domain pool is implemented by Self-Organizing Map. Each domain block
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Hsu, Hsuanming, and 許軒銘. "Vector Quantization Based On Self-Organizing Map." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/87584128893710536844.

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碩士<br>義守大學<br>資訊工程學系<br>100<br>Vector quantization has the advantages of high compression ratio and fast decompression, but in a codebook generation and encoding process must be a global search, making the coding process lengthy. If we can effectively reduce the search range of the codebook generation and encoding will be able to reduce the time spent by the codebook generation and encoding. On the other hand, the traditional vector quantization to generate codebook method that is using the LBG algorithm. The initialization of codebook is very important. What if the initialization is selected
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Liao, Wen-Chung, and 廖文忠. "Extended Self-Organizing Map for Transactional Data." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/95662897650762158331.

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博士<br>國立雲林科技大學<br>管理研究所博士班<br>100<br>In many application domains, transactions are the records of personal activities. Transactions always reveal personal behavior customs, so clustering the transactional data can divide individuals into different segments. Transactional data are often accompanied with a concept hierarchy, which defines the relevancy among all of the possible items in transactional data. However, most of clustering methods for transactional data ignore the existing of the concept hierarchy. Owing to the lack of the relevancy provided by the concept hierarchy, clustering algori
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Wang, Sheng-Hsuan, and 王勝玄. "Clustering of Self-Organizing Map on Mixed Data." Thesis, 2005. http://ndltd.ncl.edu.tw/handle/95452369784589056271.

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碩士<br>國立雲林科技大學<br>資訊管理系碩士班<br>93<br>The visualization-induced SOM (ViSOM) is a non-linear multi-dimensional projection method, extended from self-organizing map (SOM). It overcomes the drawbacks that the structure of the clusters may not be apparent and the nodes often spread around the 2-D map in the SOM. The objective of the ViSOM is to preserve the data structure as well as the topology as faithfully as possible. Even so, it still cannot express reasonably the distance or similarity of categorical data and preserve the structure of categorical data. In this study, the extended ViSOM is prop
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Chen, De-Hua, and 陳德華. "Self-Organizing Map Networks for Mixed Feature Data." Thesis, 2003. http://ndltd.ncl.edu.tw/handle/4psqvb.

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碩士<br>中原大學<br>應用數學研究所<br>91<br>In this paper we propose a Kohonen’s self-organizing map (SOM) for mixed feature (symbolic type and fuzzy type) data. The distance measures proposed in Gowda ＆ Diday[3,4], El-Sonbaty ＆ Ismail[2], Yang, Hwang ＆ Chen[9] and Yang ＆ Ko[10] are used in this paper. Based on these distance measuces we proposed the mixed feature data SOM (MFD-SOM). We then propose a modified type of MFD-SOM method, called the modified self-organizing map for mixed feature data (MFD-M-SOM). On the other hand, we use fuzzy-soft learning method of Wu ＆ Yang[8], and then create the fuzzy-sof
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Kaun, Wen-yu, and 關雯尤. "Object-Based Image Retrieval Using Self-Organizing Map." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/05698743129249762603.

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碩士<br>逢甲大學<br>資訊電機工程碩士在職專班<br>100<br>Content-based images retrieval (CBIR) has been widely used in many application fields. Yet, in commercial photography, ornaments and décor are often used to better the vision of the product as a whole. The images of the digital archive system for Taiwan flower anthography group are usually accompanied by other background objects that have nothing to do with the target plant. The background noise will decrease the precision rate of image retrieval. Therefore, we propose a method based on Visual Attention Model to extract image area of interest as training d
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Hsiao, Ya Wen, and 蕭雅文. "The construction of knowledge map in medical information with self-organizing map." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/94723697246861377148.

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碩士<br>長庚大學<br>企業管理研究所<br>97<br>The World Wide Web contains a large number of documents that are dynamic, unregulated nature and rapid proliferation. It is increasingly difficult to search for relevant medical information. Many tools have been developed to help users search for useful information, but most of them are still not efficient. The goal of this paper is to describe an architecture designed to integrate text mining, an automatic thesaurus, and Growing Hierarchical Self-Organizing Map (GHSOM) technologies to provide searchers with fine grained results. Thus, we present a content-base a
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Tew, Chee-Yuen, and 趙志運. "A Self-Organizing Feature-Map-Based Neuro-Fuzzy System." Thesis, 2001. http://ndltd.ncl.edu.tw/handle/85585354995827620877.

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碩士<br>淡江大學<br>電機工程學系<br>89<br>One of the challenges that arise in designing a fuzzy system is the trade-off between computational efficiency and performance. Basically, the more rules, the more powerful the fuzzy system becomes. However, the price paid for the high performance is that the computational load becomes extremely large. In this thesis, the author proposes an appealing and easy solution to solve the dilemma. This thesis presents an efficient scheme for fuzzy modeling by using the Kohonen’s self-organizing feature map (SOM) algorithm through its vector quantization feature and its to
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Wu, Po-hung, and 吳柏宏. "Self-Organizing Map on Auditory-Scene based Sound Segregation." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/06644794740660182920.

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碩士<br>國立交通大學<br>電信工程系所<br>97<br>During the past decade, detailed characteristics of auditory perception have been largely incorporated into speech processing algorithms to enhance their performance. For example, in the field of sound segregation, algorithms good for the condition of multiple microphones, such as independent component analysis (ICA), are often used and show satisfactory performance. However, the truth is human has no problems in segregating mixed sounds with only one ear. In this thesis, we design such a monaural speech segregation system based on an auditory perceptual model.
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Wu, Chih-Ting, and 吳智婷. "Using Self-organizing Map to Diagnose Abnormal Engineering Change." Thesis, 2013. http://ndltd.ncl.edu.tw/handle/uggtke.

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碩士<br>德明財經科技大學<br>資訊管理系<br>102<br>Engineering change can’t be avoided in the product life cycle. It will impact the enterprise profitability. Using Self-organizing Map and engineering change history information was established one model. It will diagnose and monitor engineering change for the enterprise. The product life cycle is 3-6 months in the case. The four months for historical data per group in the experiment, one was selected from January-April (2343 records) of control group, others were selected from May to August (3642 records) and from September to December (3864 records) for the e
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Kao, Huey-Shan, and 高慧珊. "Estimation of Evaporation using a Self-Organizing Map Network." Thesis, 2007. http://ndltd.ncl.edu.tw/handle/68323293614423494909.

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碩士<br>國立臺灣大學<br>生物環境系統工程學研究所<br>95<br>The phenomenon of evaporation is an important factor that affects the distribution of water in hydrological cycle and plays a key role in agriculture and water resource management. The tranditional evaporation formulas usally neglect the non-linear characteristics in the nature. In this study we propose the self-organizing map(SOM) network to estimate daily evaporation. First, the daily meteorological data from climate gauges were collected as inputs of the SOM and then classified into topology map based on their similarities to investigate their potential
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Chen, Jiun-Hung, and 陳俊宏. "Lips detection using self-organizing map and reinforcement learning." Thesis, 1999. http://ndltd.ncl.edu.tw/handle/28663252445109968468.

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碩士<br>國立臺灣大學<br>資訊工程學研究所<br>87<br>Traditional lips detection methods consist of a binary classifiers which can classify lips and nonlips followed by some search algorithms. The search algorithms may depend on some face anatomatical information or heuristics. They do not learn any structural inforamiton while searching. A new lips detection approach is proposed. It solves classificaition and search at the same time based on structural infomation in faces. There are three main parts in this proposed approach. First, face detection is based on color and shape information and autocorrelation funct
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Chen, Wei-Yi, and 陳崴逸. "Application of Self-Organizing Map to Option Implied Volatility." Thesis, 2007. http://ndltd.ncl.edu.tw/handle/03620076200903578968.

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碩士<br>國立交通大學<br>資訊管理研究所<br>95<br>In this study we investigate the lead-lag relations between the index option market and the stock market at the aggregate level. We could forecast the fluctuation of Taiwan Stock Market Index if the relations did exist. We apply the diagram constructed by volatility, the combination of the implied volatility of call and put, to represent the option market’s view for future stock market movements and discover their relations. Investors would long call when they expect the future price of spot market to soar. Thus, the implied volatility of call would rising. If
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Tseng, Shih-Yu, and 曾士育. "Knowledge Discovery with Self-Organizing Map in Investment Strategy." Thesis, 2003. http://ndltd.ncl.edu.tw/handle/81886226686155662648.

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碩士<br>國立高雄第一科技大學<br>資訊管理所<br>91<br>Financial investment is a knowledge-intensive industry. In the past years, with the electronic transaction technology advances, vast amount of transaction data have been collected and the emergence of knowledge discovery technology sheds light toward building up a financial investment decision support system. Data of financial markets are essentially time-series which bring more challenges than the traditional discrete data for uncovering the hidden knowledge. In this research, Taifex Index in Taiwan Futures Exchange K-chart patterns as the target dataset, we
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Liao, Jyun Jie, and 廖俊傑. "Application of Dynamic Self-Organizing Map in Skeleton Extraction." Thesis, 2006. http://ndltd.ncl.edu.tw/handle/56992927686132474577.

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碩士<br>南台科技大學<br>資訊工程系<br>94<br>Skeleton shape extraction technique was widely adopted in many application such as object modeling、character recognition、machine vision and computer animation .The thinning process always be used in skeleton extraction, but it often distorts the local shapes of an observed pattern. This is an inherent defect for all thinning algorithms. Therefore, a Dynamic Self-Organizing Map(DSOM) was proposed to extract skeleton precisely. But the process speed of DSOM is too slow. In order to speed up the process speed, the methods of feature-points estimation and area segmen
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Hsieh, Ming-Hsun, and 謝明勳. "Using Hierarchical Modified Self-Organizing Map in Skeleton Extraction." Thesis, 2004. http://ndltd.ncl.edu.tw/handle/12725168864478341551.

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碩士<br>南台科技大學<br>電子工程系<br>92<br>骨格抽出の技術はたくさん応用領域に広く採用されています。たどえばオブジェクト指向モデリング技術 (object modeling)、文字識別(character recognition)及びコンピュータアニメショーン(computer animation)などいろいろな応用領域に採用されています。しかし、伝統のthinningで抽出された骨格はいつも要らないの支線を分岐し、交差点の場合も変形を出ってくる事がありますから、特徴の獲得は不安定になります。だから、本論文では、「階層式修正型自己組織化マップ」を提出してこのようなの問題を解決する。 「階層式修正型自己組織化マップ(HMSOM)」はSOMとMSOMの二つの層から構成する。それで、第１、２層のネットワークとコホネンのSOMは同じ構造であり、二つの入力層と出力層から構成する。第１層では、SOMによってパターンの画素を入力データに。そして、前処理でニューロンのN個の数を概算し、出力ニューロンと画素の位置関係を考慮して、競合学習の基礎から、パターンをサブパターンにN個分割する。第２層では、１つづづのサブパターンをMSOMネットワークに入力させるし、ニューロンの数を１つにする。最後は、MSOMの可増加ニューロン数の特性によって、第１層の出力ニューロン数の
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