In this work, Self Organizing Map (SOM) is used in order to detect and classify the broken rotor bars and misalignment type mechanical faults that often occur in induction motors which are widely used in industry. The feature vector samples are extracted from the sampled line current of motors with fault and healthy one. These samples are the poles of the AR model which is obtained from the spe...

Bankruptcy prediction is one of the major business classification problems. The main purpose of this study is to investigate Kohonen self-organizing feature map in term of performance accuracy in the area of bankruptcy prediction.  A sample of 108 firms listed in Tehran Stock Exchange is used for the study. Our results confirm that Kohonen network is a robust model for predicting bankruptcy in ...

during an 11 days mission in february 2000 the shuttle radar topography mission (srtm) collected data over 80% of the earth's land surface, for all areas between 60 degrees n and 56 degrees s latitude. since srtm data became available, many studies utilized them for application in topography and morphometric landscape analysis. exploiting srtm data for recognition and extraction of topographic ...

Discovering the inherent structure in data has become one of the major challenges in data mining applications. It requires the development of stable and adaptive models that are capable of handling the typically very high-dimensional feature spaces. In this paper we present the Growing Hierarchical Self-Organizing Map (GH-SOM), a neural network model based on the self-organizing map. The main f...

In this paper, an innovative method for estimating mass functions using Kohonen’s Self Organizing Map is proposed. Our approach allows a smart mass belief assignment, not only for simple hypotheses, but also for disjunctions and conjunctions of hypotheses. This new method is of interest for solving estimation mass functions problems where a large quantity of multi-variate data is available. Ind...

Texture analysis has a wide range of real-world applications. This paper presents a novel technique for texture feature extraction and compares its performance with a number of other existing techniques using a benchmark image database. The proposed feature extraction technique uses 2 D D R transform and self-organizing map (SOM). A combination of 2D-DFT and SOM with optimal parameter settings ...

In this paper a novel framework is presented for interactive feature-based retrieval and visualization of human statues, using depth sensors for mobile devices. A skeletal model is fitted to the depth image of a statue or human body in general and is used as a feature vector that captures the pose variations in a given collection of skeleton data. A scaleand twistinvariant distance function is ...

We present a system for content-based retrieval of perceptually similar sound events in audio documents (‘sound spotting’, using a query by example. The system consists of three discrete stages: a front-end for feature extraction, a self-organizing map, and a pattern matching unit. Our paper introduces the approach, describes the separate modules and discusses some preliminary results and futur...