hot-wire spirometer uses a constant temperature anemometer (cta) for its operation. the working principle of cta, used for the measurement of fluid velocity and flow turbulence, is based on convective heat transfer from a hot-wire sensor to a fluid being measured. the calibration curve of a cta is nonlinear and cannot be easily extrapolated beyond its calibration range. therefore, a method for ...

The S-Map is a network with a simple learning algorithm that combines the self-organization capability of the Self-Organizing Map (SOM) and the probabilistic interpretability of the Generative Topographic Mapping (GTM). The simulations suggest that the SMap algorithm has a stronger tendency to self-organize from random initial configuration than the GTM. The S-Map algorithm can be further simpl...

In this paper we present a novel system that can automatically mark up text documents into XML. The system uses the Self-Organizing Map (SOM) algorithm to organize marked documents on a map so that similar documents are placed on nearby locations. Then by using the inductive learning algorithm C5, it automatically generates and applies the markup rules from the nearest SOM neighbours of an unma...

This article describes the implementation of a system that is able to organize vast document collections according to textual similarities. It is based on the self-organizing map (SOM) algorithm. As the feature vectors for the documents statistical representations of their vocabularies are used. The main goal in our work has been to scale up the SOM algorithm to be able to deal with large amoun...

The continuous growth in the size and use of the Internet is creating difficulties in the search for information. A sophisticated method to organize the layout of the information and assist user navigation is therefore particularly important. In this paper, we evaluate the feasibility of using a self-organizing map (SOM) to mine web log data and provide a visual tool to assist user navigation. ...

We present an efficient approach to forming feature maps. The method involves three stages. In the first stage, we use the K-means algorithm to select N2 (i.e., the size of the feature map to be formed) cluster centers from a data set. Then a heuristic assignment strategy is employed to organize the N2 selected data points into an N x N neural array so as to form an initial feature map. If the ...

This paper proposes an extension of an SOM called the “SOM of SOMs,” or SOM, in which objects to be mapped are self-organizing maps. In SOM, each nodal unit of a conventional SOM is replaced by a function module of SOM. Therefore, SOM can be regarded as a variation of a modular network SOM (mnSOM). Since each child SOM module in SOM is trained to represent an individual map, the parent map in S...

The labyrinthine abundance of educational resources on the Web has greatly expanded the challenge of helping students find, organize, and use resources that will best match their individual goals, interests, and current knowledge. Map-based navigation, using technologies such as the Self-Organizing Maps (SOM), is one solution to this growing challenge. However, as the number of documents organi...

The availability of linguistic corpora in electronic form has made it possible to make various kinds of computer-based analyses on them. The use of Self-Organizing Map (SOM) in the analysis and visualization of various aspects of textual material is outlined. The basic approach for creating maps of lexical items, documents, or set of languages or dialects is described with reference to original...

Kohonen’s Self-Organizing Map (SOM) is a general unsupervised tool for ordering highdimensional statistical data so that neighboring nodes on the map represent similar inputs. Often the SOM is applied to numerical data in application areas like pattern recognition, signal processing, and multivariate statistical analysis. The SOM can also be used to find statistical similarities between symbols...