Prediction of surface air temperatures by neural network, example based on three-year temperature monitoring at Spořilov station.

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985530%3A_____%2F03%3A03030011" target="_blank" >RIV/67985530:_____/03:03030011 - isvavai.cz</a>

Result on the web

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DOI - Digital Object Identifier

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Result language

angličtina

Original language name

Prediction of surface air temperatures by neural network, example based on three-year temperature monitoring at Spořilov station.

Original language description

Artificial time-delay feed-forward neural networks with one hidden layer and error back-propagation learning are used to predict surface air temperatures for six hours up to one day. The networks were trained and tested with the use of data covering a total of 26280 hours monitored in the period 1998-2000 in location Spořilov (suburban area of Prague).

Czech name

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Czech description

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Type

J_x - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)

CEP classification

DB - Geology and mineralogy

OECD FORD branch

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Project

<a href="/en/project/IAA3012005" target="_blank" >IAA3012005: Recent Climate Change and Its Contingent Anthropogenic Component Revealed by Inversion of Present Temperature Data Measured in Boreholes</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>Z - Vyzkumny zamer (s odkazem do CEZ)

Publication year

2003

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Studia geophysica et geodaetica

ISSN

0039-3169

e-ISSN

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Volume of the periodical

47

Issue of the periodical within the volume

1

Country of publishing house

CZ - CZECH REPUBLIC

Number of pages

12

Pages from-to

173-184

UT code for WoS article

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EID of the result in the Scopus database

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