Autonomous underwater vehicles (AUVs) have great advantages for activities in deep sea, and expected as the attractive tool. However, AUVs have various problems which should be solved. In this paper, the Self-Organizing Map (SOM) is applied as the clustering method for the navigation system. The SOM is known as one of the effective methods to extract the principle feature from many parameters a...

Cluster structure of gene expression data obtained from DNA microarrays is analyzed and visualized with the Self-Organizing Map (SOM) algorithm. The SOM forms a non-linear mapping of the data to a two-dimensional map grid that can be used as an exploratory data analysis tool for generating hypotheses on the relationships, and ultimately of the function of the genes. Similarity relationships wit...

We propose a neural preprocess approach for video-based gesture recognition system. Second-order neural network (SONN) and self-organizing map (SOM) are employed for extracting moving hand regions and for normalizing motion features respectively. The SONN is more robust to noise than frame difference technique. Obtained velocity feature vectors are translated into normalized feature space by th...

The self-organizing map (SOM) represents an open set of input samples by a topologically organized, finite set of models. In this paper, a new version of the SOM is used for the clustering, organization, and visualization of a large database of symbol sequences (viz. protein sequences). This method combines two principles: the batch computing version of the SOM, and computation of the generaliz...

In this paper, a new approach to Mediterranean Water Eddy border detection is proposed. Kohonen self-organizing maps (SOM) are used as data mining tools to cluster image pixels through an unsupervised process. The clusters are visualized on the SOM internal map. From the visualization, the borders can be detected through an interactive way. As a result, interesting patterns are visible on the i...

This paper presents a combination of Self-Organizing Map (SOM) approach and navigation functions in the Traveling Salesman Problem with segment goals where paths between goals have to respect obstacles. Hence, the problem is called multi-goal path planning. The problem arises from the inspection planning, where a path from which all points of the given polygonal environment have to be “seen”. T...

The paper presents a new method for adaptive selection of Self-Organizing Map (SOM) self-training endpoint. A method is based on the estimation of the newly introduced parameter ∆init and the learning depth parameter κ. In order to propose an optimal range of κ values, the influence of the selected learning depth parameter to the performance of SOM was tested experimentally using input data wit...

Self-Organizing Maps (SOM) are considered by many to be black boxes because the results are often non-intuitive. Our research takes the multidimensional output from a successful intrusion detecting SOM and displays it in novel full color and 3D formats, with landscape features similar to an island, that assist in understanding the SOM results. This paper describes the visual data mining from th...

In this paper, we describe the formatting guidelines for IJCA Journal Submission. The SOM, for kohonen Self Organizing Map, has proven to be a classifier of high caliber in the field of speech recognition signals breasts. Thus, several versions and enhancements were applied on this tool such as recurrent SOM 'RSOM', the growing recurrent SOM 'GRSOM' and the growing hierarchi...

This paper presents a comprehensive, corpus-based study of adjectival concepts. An adjectival concept is a semantic class of adjectives, for example, “adjectives which express feeling”. We represent adjectival concepts by abstract nouns (such as “feeling”), and extract instances where abstract nouns are modified by adjectives (such as “happy feeling”) from a large corpus of Japanese newspaper a...