TAPPI JOURNAL PEER REVIEWED PAPER Analysis of pulping data using the self-organizing map
نویسنده
چکیده
Analysis of process data makes it possible to obtain useful information of processes or phenomena that are analytically difficult to deal with. To demonstrate the possibilities of this kind of approach, an analysis of the faults that occurred in a continuous digester is presented. The process data are fed to an artificial neural network, the Self-Organizing Map (SOM), which is used to form visual presentations of the data. By interpreting these visualizations, the reason for the faults can be determined.
منابع مشابه
Classification of Streaming Fuzzy DEA Using Self-Organizing Map
The classification of fuzzy data is considered as the most challenging areas of data analysis and the complexity of the procedures has been obstacle to the development of new methods for fuzzy data analysis. However, there are significant advances in modeling systems in which fuzzy data are available in the field of mathematical programming. In order to exploit the results of the researches on ...
متن کاملNGTSOM: A Novel Data Clustering Algorithm Based on Game Theoretic and Self- Organizing Map
Identifying clusters is an important aspect of data analysis. This paper proposes a noveldata clustering algorithm to increase the clustering accuracy. A novel game theoretic self-organizingmap (NGTSOM ) and neural gas (NG) are used in combination with Competitive Hebbian Learning(CHL) to improve the quality of the map and provide a better vector quantization (VQ) for clusteringdata. Different ...
متن کاملLandforms identification using neural network-self organizing map and SRTM data
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 ...
متن کاملGait Based Vertical Ground Reaction Force Analysis for Parkinson’s Disease Diagnosis Using Self Organizing Map
The aim of this work is to use Self Organizing Map (SOM) for clustering of locomotion kinetic characteristics in normal and Parkinson’s disease. The classification and analysis of the kinematic characteristics of human locomotion has been greatly increased by the use of artificial neural networks in recent years. The proposed methodology aims at overcoming the constraints of traditional analysi...
متن کاملA Modfied Self-organizing Map Neural Network to Recognize Multi-font Printed Persian Numerals (RESEARCH NOTE)
This paper proposes a new method to distinguish the printed digits, regardless of font and size, using neural networks.Unlike our proposed method, existing neural network based techniques are only able to recognize the trained fonts. These methods need a large database containing digits in various fonts. New fonts are often introduced to the public, which may not be truly recognized by the Opti...
متن کامل