نتایج جستجو برای: organizing map som neural networks finally

تعداد نتایج: 1198270  

2013
P Arumugam Christy

Web Usage Mining becomes a vital aspect in network traffic analysis. Previous study on Web usage mining using a synchronized Clustering, Neural based approach has shown that the usage trend analysis very much depends on the performance of the clustering of the number of requests. Self Organizing Networks is useful for representation of building unsupervised learning, clustering, and Visualizati...

2008
Esteban J. Palomo Enrique Domínguez Rafael Marcos Luque Baena José Muñoz

Detecting network intrusions is becoming crucial in computer networks. In this paper, an Intrusion Detection System based on a competitive learning neural network is presented. Most of the related works use the self-organizing map (SOM) to implement an IDS. However, the competitive neural network has less complexity and it is faster than the SOM, achieving similar results. In order to improve t...

Journal: :Inf. Sci. 2000
Sung-Bae Cho

Combining multiple models has been recently exploited for the development of reliable neural networks. This paper introduces a structure-adaptive self-organizing map (SOM) which can adapt the structure as well as the weights, and presents a method to improve the performance by combining the multiple maps. The structure-adaptive SOM places the nodes of prototype vectors into the pattern space pr...

2012
Hsin-Chang Yang Chung-Hong Lee

The self-organizing map (SOM) model is a well-known neural network model with wide spread of applications. The main characteristics of SOM are two-fold, namely dimension reduction and topology preservation. Using SOM, a high-dimensional data space will be mapped to some low-dimensional space. Meanwhile, the topological relations among data will be preserved. With such characteristics, the SOM w...

2002
Barbara Hammer Alessio Micheli Alessandro Sperduti

Self-organization constitutes an important paradigm in machine learning with successful applications e.g. in dataand web-mining. Most approaches, however, have been proposed for processing data contained in a fixed and finite dimensional vector space. In this article, we will focus on extensions to more general data structures like sequences and tree structures. Various modifications of the sta...

2011
Vikas Chaudhary Anil K. Ahlawat Xinjian Qiang Guojian Cheng Zheng Wang Ziqi Song Jinquan Yang Rongfang Gao Tianshi Liu Jiaxin Han

This paper gives an overview of some classical Growing Neural Networks (GNN) using soft competitive learning. In soft competitive learning each input signal is characterized by adapting in addition to the winner also some other neurons of the network. The GNN is also called the ANN with incremental learning. The artificial neural networks (ANN) mapping capability depends on the number of layers...

2011
Dennis Ippoliti Xiaobo Zhou

 Anomaly detection and misuse detection are two major types of network intrusion detection systems.  Machine learning approaches have been used for anomaly detection. In particular, approaches based on self-organizing maps (SOMs) of artificial neural networks have shown effectiveness at identifying “unknown” attacks.  Effectiveness of using traditional SOM models is limited by the static nat...

Journal: :IEEE transactions on neural networks 1999
Dong-Chul Park Young-June Woo

An edge preserving image compression algorithm based on an unsupervised competitive neural network is proposed. The proposed neural network, the called weighted centroid neural network (WCNN), utilizes the characteristics of image blocks from edge areas. The mean/residual vector quantization (M/RVQ) scheme is utilized in this proposed approach as the framework of the proposed algorithm. The edg...

1992
Tomas Nordström

Self organizing maps (SOM) are a class of artificial neural network (ANN) models developed by Kohonen. There are a number of variants, where the self organizing feature map (SOFM) is one of the most used ANN models with unsupervised learning. Learning vector quantifiers (LVQ) is another group of SOM which can be used as very efficient classifiers. SOM have been used in a variety of fields, e.g....

Journal: :CoRR 2003
Juan Julián Merelo Guervós Beatriz Prieto Fatima Rateb Fernando Tricas García

Websites of a particular class form increasingly complex networks, and new tools are needed to map and understand them. A way of visualizing this complex network is by mapping it. A map highlights which members of the community have similar interests, and reveals the underlying social network. In this paper, we will map a network of websites using Kohonen’s self-organizing map (SOM), a neural-n...

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