Predicting PM10 Concentrations Using Fuzzy Kriging, In book: Hybrid Artificial Intelligent Systems

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989592%3A15310%2F15%3A33158123" target="_blank" >RIV/61989592:15310/15:33158123 - isvavai.cz</a>

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Predicting PM10 Concentrations Using Fuzzy Kriging, In book: Hybrid Artificial Intelligent Systems

Popis výsledku v původním jazyce

The prediction of meteorological phenomena is usually based on the creation of surface from point sources using the certain type of interpolation algorithms. The prediction standardly does not incorporate any kind of uncertainty, either in the calculation itself or its results. The selection of the interpolation method, as well as its parameters depend on the user and his experiences. That does not mean the problem necessarily. However, in the case of the spatial distribution modelling of potentially dangerous air pollutants, the inappropriately selected parameters and model may cause inaccuracies in the results and their evaluation. In this contribution, we propose the prediction using fuzzy kriging that allows incorporating the experts knowledge. Wecombined previously presented approaches with optimization probabilistic metaheuristic method simulated annealing. The application of this approach in the real situation is presented on the prediction of PM10 particles in the air in the C

Název v anglickém jazyce

Predicting PM10 Concentrations Using Fuzzy Kriging, In book: Hybrid Artificial Intelligent Systems

Popis výsledku anglicky

The prediction of meteorological phenomena is usually based on the creation of surface from point sources using the certain type of interpolation algorithms. The prediction standardly does not incorporate any kind of uncertainty, either in the calculation itself or its results. The selection of the interpolation method, as well as its parameters depend on the user and his experiences. That does not mean the problem necessarily. However, in the case of the spatial distribution modelling of potentially dangerous air pollutants, the inappropriately selected parameters and model may cause inaccuracies in the results and their evaluation. In this contribution, we propose the prediction using fuzzy kriging that allows incorporating the experts knowledge. Wecombined previously presented approaches with optimization probabilistic metaheuristic method simulated annealing. The application of this approach in the real situation is presented on the prediction of PM10 particles in the air in the C

Druh

C - Kapitola v odborné knize

CEP obor

DE - Zemský magnetismus, geodesie, geografie

OECD FORD obor

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Projekt

<a href="/cs/project/EE2.3.20.0170" target="_blank" >EE2.3.20.0170: Budování výzkumně-vzdělávacího týmu v oblasti modelování přírodních jevů a využití geoinformačních systémů, s vazbou na zapojení do mezinárodních sítí a programů.</a><br>

Návaznosti

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

Rok uplatnění

2015

Kód důvěrnosti údajů

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

Název knihy nebo sborníku

Hybrid Artificial Intelligent Systems

ISBN

978-3-319-19643-5

Počet stran výsledku

11

Strana od-do

371-381

Počet stran knihy

740

Název nakladatele

Springer Basel

Místo vydání

Basel

Kód UT WoS kapitoly

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