Sökning: "Self Organizing Map"

Visar resultat 1 - 5 av 13 avhandlingar innehållade orden Self Organizing Map.

1. 1. Fluid Power Applications Using Self-Organising Maps in Condition Monitoring

   Författare :Anders Zachrison; Jan-Ove Palmberg; Magnus Sethson; Richard Burton; Linköpings universitet; []
   Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Fluid power; pneumatic; self-organizing maps; condition monitoring; Signal processing; Signalbehandling;

   Sammanfattning : Condition monitoring of systems and detection of changes in the systems are of significant importance for an automated system, whether it is for production, transport, amusement, or any other application. Although condition monitoring is already widely used in machinery, the need for it is growing, especially as systems become increasingly autonomous and self-contained. LÄS MER

3. 2. Morphometric and Landscape Feature Analysis with Artificial Neural Networks and SRTM data : Applications in Humid and Arid Environments

   Författare :Amir Houshang Ehsani; Friedrich Quiel; Wolfgang Wagner; KTH; []
   Nyckelord :Self Organizing Map; Neural Network; Morphometric Feature; Landscape; Yardang; Lut Desert; Potential natural vegetation; geoecosystem; Landform; Landsat ETM ; Morphometric Parameters; SRTM; Resolution; Curvatures; DEM.; TECHNOLOGY; TEKNIKVETENSKAP;

   Sammanfattning : This thesis presents a semi-automatic method to analyze morphometric features and landscape elements based on Self Organizing Map (SOM) as an unsupervised Artificial Neural Network algorithm in two completely different environments: 1) the Man and Biosphere Reserve “Eastern Carpathians” (Central Europe) as a complex mountainous humid area and 2) Lut Desert, Iran, a hyper arid region characterized by repetition of wind-eroded features. In 2003, the National Aeronautics and Space Administration (NASA) released the SRTM/ SIR-C band data with 3 arc seconds (approx. LÄS MER

4. 3. Rainfall-Runoff Modelling Using Artificial Neural Networks (ANNs)

   Författare :Aman Mohammad Kalteh; Avdelningen för Teknisk vattenresurslära; []
   Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Hydrogeology; geographical and geological engineering; Hydrogeologi; teknisk geologi; teknisk geografi; Self-organizing map; Feed-forward multilayer perceptron; Forecasting; Hydrological modelling; Missing values; Rainfall-runoff modelling; Estimation; Artificial neural networks;

   Sammanfattning : Over the last decades or so, artificial neural networks (ANNs) have become one of the most promising tools for modelling hydrological processes such as rainfall-runoff processes. In most studies, ANNs have been demonstrated to show superior result compared to the traditional modelling approaches. LÄS MER

5. 4. Modelling and controlling an offset lithographic printing process

   Författare :Cristofer Englund; Högskolan i Halmstad; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Neural networks; Self-organizing map; Data mining; Outlier detection; Committee; Multiple models; Colour print control; Image analysis; Bildanalys;

   Sammanfattning : The objective of this thesis is to provide methods for print quality enhancements in an offset lithographic printing proess. Various parameters characterising the print quality are recognised, however, in this work print quality is defined as the deviation of the amount of ink in a sample image from the reference print. LÄS MER

7. 5. Modelling the offset lithographic printing process

   Författare :Cristofer Englund; Högskolan i Halmstad; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; Neural networks; Self-organizing map; Data mining; Outlier detection; Leverages; Committee; Adaptive modelling; Image analysis; Bildanalys;

   Sammanfattning : A concept for data management and adaptive modelling of the offset lithographic printing process is proposed. Artificial neural networks built from historical process data are used to model the offset printing process aiming to develop tools for online ink flow control. LÄS MER