Air quality assessment using neural networks and fuzzy logic

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216275%3A25410%2F11%3A39892224" target="_blank" >RIV/00216275:25410/11:39892224 - isvavai.cz</a>

Výsledek na webu

—

DOI - Digital Object Identifier

—

Jazyk výsledku

angličtina

Název v původním jazyce

Air quality assessment using neural networks and fuzzy logic

Popis výsledku v původním jazyce

Traditional air quality assessment is realized using air quality indices which are determined as mean values of selected air pollutants. Thus, air quality assessment depends on strictly given limits without taking into account specific local conditions and synergic relations between air pollutants and other meteorological factors. The stated limitations can be eliminated, e.g. using systems based on neural networks and fuzzy logic. Therefore, the paper presents a design of a model for air quality assessment based on a combination of Kohonen's self-organizing feature maps and fuzzy logic neural networks. The model makes it possible to analyze the structure of data, to find localities with similar air quality and to interpret the classification results by means of fuzzy logic. Due to its generalization ability, it is also possible to classify unknown localities into classes assessing their air quality.

Název v anglickém jazyce

Air quality assessment using neural networks and fuzzy logic

Popis výsledku anglicky

Traditional air quality assessment is realized using air quality indices which are determined as mean values of selected air pollutants. Thus, air quality assessment depends on strictly given limits without taking into account specific local conditions and synergic relations between air pollutants and other meteorological factors. The stated limitations can be eliminated, e.g. using systems based on neural networks and fuzzy logic. Therefore, the paper presents a design of a model for air quality assessment based on a combination of Kohonen's self-organizing feature maps and fuzzy logic neural networks. The model makes it possible to analyze the structure of data, to find localities with similar air quality and to interpret the classification results by means of fuzzy logic. Due to its generalization ability, it is also possible to classify unknown localities into classes assessing their air quality.

Druh

D - Stať ve sborníku

CEP obor

IN - Informatika

OECD FORD obor

—

Projekt

<a href="/cs/project/SP%2F4I2%2F60%2F07" target="_blank" >SP/4I2/60/07: Indikátory pro hodnocení a modelování internakcí mezi životním prostředím, ekonomikou a sociálními souvislostmi</a><br>

Návaznosti

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

Rok uplatnění

2011

Kód důvěrnosti údajů

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

Název statě ve sborníku

Recent Researches in Environment, Energy Planning and Pollution

ISBN

978-1-61804-012-1

ISSN

—

e-ISSN

—

Počet stran výsledku

6

Strana od-do

49-54

Název nakladatele

WSEAS Press

Místo vydání

Atény

Místo konání akce

Iasi

Datum konání akce

1. 7. 2011

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

—