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  3. Billedbehandling: systemer og teknologi

Nonlinear Dimensionality Reduction Techniques

- A Data Structure Preservation Approach
Af: Denys Dutykh, Benoit Colange, Sylvain Lespinats Engelsk Paperback

Nonlinear Dimensionality Reduction Techniques

- A Data Structure Preservation Approach
Af: Denys Dutykh, Benoit Colange, Sylvain Lespinats Engelsk Paperback
Tjek vores konkurrenters priser
This book proposes tools for analysis of multidimensional and metric data, by establishing a state-of-the-art of the existing solutions and developing new ones. It mainly focuses on visual exploration of these data by a human analyst, relying on a 2D or 3D scatter plot display obtained through Dimensionality Reduction. 

Performing diagnosis of an energy system requires identifying relations between observed monitoring variables and the associated internal state of the system. Dimensionality reduction, which allows to represent visually a multidimensional dataset, constitutes a promising tool to help domain experts to analyse these relations. This book reviews existing techniques for visual data exploration and dimensionality reduction such as tSNE and Isomap, and proposes new solutions to challenges in that field. 

In particular, it presents the new unsupervised technique ASKI and the supervised methods ClassNeRV and ClassJSE. Moreover, MING, a new approach for local map quality evaluation is also introduced. These methods are then applied to the representation of expert-designed fault indicators for smart-buildings, I-V curves for photovoltaic systems and acoustic signals for Li-ion batteries.


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This book proposes tools for analysis of multidimensional and metric data, by establishing a state-of-the-art of the existing solutions and developing new ones. It mainly focuses on visual exploration of these data by a human analyst, relying on a 2D or 3D scatter plot display obtained through Dimensionality Reduction. 

Performing diagnosis of an energy system requires identifying relations between observed monitoring variables and the associated internal state of the system. Dimensionality reduction, which allows to represent visually a multidimensional dataset, constitutes a promising tool to help domain experts to analyse these relations. This book reviews existing techniques for visual data exploration and dimensionality reduction such as tSNE and Isomap, and proposes new solutions to challenges in that field. 

In particular, it presents the new unsupervised technique ASKI and the supervised methods ClassNeRV and ClassJSE. Moreover, MING, a new approach for local map quality evaluation is also introduced. These methods are then applied to the representation of expert-designed fault indicators for smart-buildings, I-V curves for photovoltaic systems and acoustic signals for Li-ion batteries.


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Produktdetaljer
Sprog: Engelsk
Sider: 247
ISBN-13: 9783030810283
Indbinding: Paperback
Udgave:
ISBN-10: 3030810283
Kategori: Billedbehandling: systemer og teknologi
Udg. Dato: 4 dec 2022
Længde: 0mm
Bredde: 155mm
Højde: 235mm
Forlag: Springer Nature Switzerland AG
Oplagsdato: 4 dec 2022
Forfatter(e): Denys Dutykh, Benoit Colange, Sylvain Lespinats
Forfatter(e) Denys Dutykh, Benoit Colange, Sylvain Lespinats

Kategori Billedbehandling: systemer og teknologi

ISBN-13 9783030810283

Sprog Engelsk

Indbinding Paperback

Sider 247

Udgave

Længde 0mm

Bredde 155mm

Højde 235mm

Udg. Dato 4 dec 2022

Oplagsdato 4 dec 2022

Forlag Springer Nature Switzerland AG

Kategori sammenhænge