Cluster Analysis Aplications in Matlab Using Kohonen Network
نویسندگان
چکیده
This paper deals with the Kohonen Self-organizing maps for cluster analysis applications. The cluster analysis represents a group of methods whose aim is to classify the objects into clusters. For solving cluster analysis applications many new algorithms using neural networks have been used. This paper describes the use of an advanced method of neural network represented by Kohonen self-organizing maps. Also some examples of applications for cluster analysis in Matlab are presented.
منابع مشابه
Design of Kohonen Self-organizing Map with Reduced Structure
This paper deals with design of optimal structure of Kohonen Self-organizing maps for cluster analysis applications. The cluster analysis represents a group of methods whose aim is to classify the objects into clusters. There have been many new algorithms solving cluster analysis applications, which used neural networks. This paper deals with the use of advanced methods of neural networks repre...
متن کاملCluster Analysis and Neural Network
The cluster analysis represents a group of methods whose aim is to classify the investigated objects into clusters. There have been suggested many new algorithms recently. This article deals with the use of an advanced method of neural network represented by Kohonen self-organizing maps for cluster analysis and describes its basis. The software Matlab 7.1 was used to present the applications of...
متن کاملپیش بینی خصوصیات نخ ریسیده شده در ریسندگی فاستونی با استفاده از روش ترکیبی شبکه عصبی با ناظر و بدون ناظر
The uniformity of yarn is one of the major quality parameters which significantly influences on yarn characteristics, warping, weaving, and ultimately fabric production. This parameter depends on fiber properties and spinning process directly. In this study, yarn non-uniformity in a worsted spinning system was predicted by using a hybrid technique involving Kohonen's self-organized and percep...
متن کاملRecurrent and Concurrent Neural Networks for Objects Recognition
A system based on a neural network framework is considered. We used two neural networks, an Elman network [1][2] and a Kohonen (concurrent) network [3], for a categorization task. The input of the system are objects derived from three general prototypes: circle, square, polygon. We varied the size and orientation of the objects in a continuous way. The system is trained using a new algorithm, b...
متن کاملClassification of Indian meteorological stations using cluster and fuzzy cluster analysis, and Kohonen artificial neural networks
The present study deals with the application of cluster analysis, Fuzzy Cluster Analysis (FCA) and Kohonen Artificial Neural Networks (KANN) methods for classification of 159 meteorological stations in India into meteorologically homogeneous groups. Eight parameters, namely latitude, longitude, elevation, average temperature, humidity, wind speed, sunshine hours and solar radiation, are conside...
متن کامل