Buch, Englisch, 258 Seiten, Previously published in hardcover, Format (B × H): 155 mm x 235 mm, Gewicht: 482 g
Reihe: Springer Finance
with Self-Organizing Maps
Buch, Englisch, 258 Seiten, Previously published in hardcover, Format (B × H): 155 mm x 235 mm, Gewicht: 482 g
Reihe: Springer Finance
ISBN: 978-1-84996-999-4
Verlag: Springer
Self-organizing maps (SOM) have proven to be of significant economic value in the areas of finance, economic and marketing applications. As a result, this area is rapidly becoming a non-academic technology. This book looks at near state-of-the-art SOM applications in the above areas, and is a multi-authored volume, edited by Guido Deboeck, a leading exponent in the use of computational methods in financial and economic forecasting, and by the originator of SOM, Teuvo Kohonen. The book contains chapters on applications of unsupervised neural networks using Kohonen's self-organizing map approach.
Zielgruppe
Professional/practitioner
Autoren/Hrsg.
Fachgebiete
- Wirtschaftswissenschaften Volkswirtschaftslehre Volkswirtschaftslehre Allgemein Ökonometrie
- Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Numerische Mathematik
- Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Angewandte Mathematik, Mathematische Modelle
- Naturwissenschaften Physik Quantenphysik Atom- und Molekülphysik
- Wirtschaftswissenschaften Betriebswirtschaft Unternehmensfinanzen Finanzierung, Investition, Leasing
- Wirtschaftswissenschaften Finanzsektor & Finanzdienstleistungen Unternehmensfinanzierung
- Naturwissenschaften Physik Thermodynamik Plasmaphysik
- Wirtschaftswissenschaften Betriebswirtschaft Wirtschaftsmathematik und -statistik
- Mathematik | Informatik EDV | Informatik Informatik
- Wirtschaftswissenschaften Finanzsektor & Finanzdienstleistungen Finanzsektor & Finanzdienstleistungen: Allgemeines
- Wirtschaftswissenschaften Finanzsektor & Finanzdienstleistungen Bankwirtschaft
Weitere Infos & Material
1: Applications.- 1 Let Financial Data Speak for Themselves.- 2 Projection of Long-term Interest Rates with Maps.- 3 Picking Mutual Funds with Self-Organizing Maps.- 4 Maps for Analyzing Failures of Small and Medium-sized Enterprises.- 5 Self-Organizing Atlas of Russian Banks.- 6 Investment Maps of Emerging Markets.- 7 A Hybrid Neural Network System for Trading Financial Markets.- 8 Real Estate Investment Appraisal of Land Properties using SOM.- 9 Real Estate Investment Appraisal of Buildings using SOM.- 10 Differential Patterns in Consumer Purchase Preferences using Self-Organizing Maps: A Case Study of China.- 2: Methodology, Tools and Techniques.- 11 The SOM Methodology.- 12 Self-Organizing Maps of Large Document Collections.- 13 Software Tools for Self-Organizing Maps.- 14 Tips for Processing and Color-coding of Self-Organizing Maps.- 15 Best Practices in Data Mining using Self-Organizing Maps.- Notes.- Author Index.
