Ozone prediction on the basis of neural networks, support vector regression and methods with uncertainty

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216275%3A25410%2F12%3A39895104" target="_blank" >RIV/00216275:25410/12:39895104 - isvavai.cz</a>

Result on the web

<a href="http://dx.doi.org/10.1016/j.ecoinf.2012.09.001" target="_blank" >http://dx.doi.org/10.1016/j.ecoinf.2012.09.001</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.ecoinf.2012.09.001" target="_blank" >10.1016/j.ecoinf.2012.09.001</a>

Result language

angličtina

Original language name

Ozone prediction on the basis of neural networks, support vector regression and methods with uncertainty

Original language description

The article presents modeling of daily average ozone level prediction by means of neural networks, support vector regression and methods based on uncertainty. Based on data measured by a monitoring station of the Pardubice micro-region, the Czech Republic, and optimization of the number of parameters by a defined objective function and genetic algorithm a model of daily average ozone level prediction in a certain time has been designed. The designed model has been optimized in light of its input parameters. The goal of prediction by various methods was to compare the results of prediction with the aim of various recommendations to micro-regional public administration management. It is modeling by means of feed-forward perceptron type neural networks, time delay neural networks, radial basis function neural networks, epsilon-support vector regression, fuzzy inference systems and Takagi-Sugeno intuitionistic fuzzy inference systems. Special attention is paid to the adaptation of the Taka

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

IN - Informatics

OECD FORD branch

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Project

Result was created during the realization of more than one project. More information in the Projects tab.

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2012

Confidentiality

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

Name of the periodical

Ecological Informatics

ISSN

1574-9541

e-ISSN

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Volume of the periodical

12

Issue of the periodical within the volume

Listopad

Country of publishing house

NL - THE KINGDOM OF THE NETHERLANDS

Number of pages

12

Pages from-to

31-42

UT code for WoS article

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EID of the result in the Scopus database

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