Air Quality Modelling by Neural Networks
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216275%3A25410%2F09%3A00009279" target="_blank" >RIV/00216275:25410/09:00009279 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Air Quality Modelling by Neural Networks
Original language description
The chapter presents the parameters design for air quality modelling. Only those parameters were selected which show low correlation dependences. Therefore, data matrix is designed where vectors characterize the districts. Further, the chapter presents the basic concepts of the Kohonen?s self-organizing feature maps (KSOFM) (unsupervised learning) and Learning Vector Quantization (LVQ) (supervised learning) neural networks.
Czech name
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Czech description
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Classification
Type
C - Chapter in a specialist book
CEP classification
IN - Informatics
OECD FORD branch
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Result continuities
Project
<a href="/en/project/SP%2F4I2%2F60%2F07" target="_blank" >SP/4I2/60/07: Indicators for assessment and simulation of interactions among environment, economics and social connections</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2009
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Book/collection name
Modelling of Selected areas of Sustainable Development by Artificial Intelligence and Soft Computing - Regional level
ISBN
978-80-247-3167-4
Number of pages of the result
18
Pages from-to
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Number of pages of the book
152
Publisher name
GRADA Publishing a.s.
Place of publication
Praha
UT code for WoS chapter
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