Будь ласка, використовуйте цей ідентифікатор, щоб цитувати або посилатися на цей матеріал: http://dspace.wunu.edu.ua/handle/316497/33243
Повний запис метаданих
Поле DCЗначенняМова
dc.contributor.authorSirola, Miki-
dc.contributor.authorTalonen, Jaakko-
dc.date.accessioned2019-03-30T08:07:52Z-
dc.date.available2019-03-30T08:07:52Z-
dc.date.issued2012-
dc.identifier.citationSirola, М. Self-Organizing Map Based Visualization Techniques and Their Assessment [Text] / Miki Sirola, Jaakko Talonen // Computing = Комп’ютинг. - 2012. - Vol. 11, is. 2. - P. 96-103.uk_UA
dc.identifier.urihttp://dspace.tneu.edu.ua/handle/316497/33243-
dc.description.abstractOur research group has been studying data-analysis based techniques in decision support and visualization. We had a long industrial research project in co-operation with a Finnish nuclear power plant Olkiluoto. We developed many decision support schemes based on Self-Organizing Map (SOM) method combined with other methodologies. Also several visualizations based on various data-analysis methods were developed. Data from the Olkiluoto plant and training simulator was used in the analysis. In this paper some of these visualizations are presented, analyzed, and assessed with a psychological framework. Measuring the information value of the visualizations is a real challenge. The developed visualizations and visualization techniques are also compared with some existing visualizations and techniques in current plants and research laboratories. The visualizations and the visualization techniques are developed further, and completely new visualizations and techniques are developed. We point out what additional value the new visualization techniques can produce. A detailed test case of using Self-Organizing Map (SOM) method with Olkiluoto plant data is presented. With this practical example the information value of this method is shown, and it is also pointed out how it can be assessed, and what are the most reliable criteria in this assessment.uk_UA
dc.publisherТНЕУuk_UA
dc.subjectself-organizing mapuk_UA
dc.subjectdata analysisuk_UA
dc.subjectneural methodsuk_UA
dc.subjectvisualizationuk_UA
dc.titleSelf-Organizing Map Based Visualization Techniques and Their Assessmentuk_UA
dc.typeArticleuk_UA
Розташовується у зібраннях:Комп'ютинг 2012 рік. Том 11. Випуск 2

Файли цього матеріалу:
Файл Опис РозмірФормат 
Sirola.pdf416.61 kBAdobe PDFПереглянути/Відкрити


Усі матеріали в архіві електронних ресурсів захищені авторським правом, всі права збережені.