Using of artificial neural network for evaluation and prediction of some drinking water quality parameters within a water distribution system

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26110%2F11%3APU91296" target="_blank" >RIV/00216305:26110/11:PU91296 - isvavai.cz</a>

Výsledek na webu

—

DOI - Digital Object Identifier

—

Jazyk výsledku

angličtina

Název v původním jazyce

Using of artificial neural network for evaluation and prediction of some drinking water quality parameters within a water distribution system

Popis výsledku v původním jazyce

The project is focus on the methods for evaluation the available historical data of water quality and the investigation of the impact for selected physical parameters of water quality and its development in a water distribution system. It will be solved by creating a model using data-driven methods to identify and predict the evolution of selected water quality parameters. The wide open used data-driven methods in water management are Multiple Linear Regression (MLR) based on the least square approach and Multi Layer Perceptron (MLP), which is an Artificial Neural Network (ANN) architecture capable of predict any continues variable. The performance of MLP and MLR are evaluated using 4-years old database set of inputs collected in the city of Našiměřice Czech Republic. The first part of the paper shows a summary of the state of the knowledge in modeling using ANN and the second part describes the collection of data and construction of the models.

Název v anglickém jazyce

Using of artificial neural network for evaluation and prediction of some drinking water quality parameters within a water distribution system

Popis výsledku anglicky

The project is focus on the methods for evaluation the available historical data of water quality and the investigation of the impact for selected physical parameters of water quality and its development in a water distribution system. It will be solved by creating a model using data-driven methods to identify and predict the evolution of selected water quality parameters. The wide open used data-driven methods in water management are Multiple Linear Regression (MLR) based on the least square approach and Multi Layer Perceptron (MLP), which is an Artificial Neural Network (ANN) architecture capable of predict any continues variable. The performance of MLP and MLR are evaluated using 4-years old database set of inputs collected in the city of Našiměřice Czech Republic. The first part of the paper shows a summary of the state of the knowledge in modeling using ANN and the second part describes the collection of data and construction of the models.

Druh

D - Stať ve sborníku

CEP obor

JM - Inženýrské stavitelství

OECD FORD obor

—

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2011

Kód důvěrnosti údajů

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

Název statě ve sborníku

JUNIORSTAV 2011

ISBN

978-80-214-4232-0

ISSN

—

e-ISSN

—

Počet stran výsledku

11

Strana od-do

243-253

Název nakladatele

VUT v Brně, Fakulta stavební

Místo vydání

Brno, ČR

Místo konání akce

Brno

Datum konání akce

4. 2. 2011

Typ akce podle státní příslušnosti

EUR - Evropská akce

Kód UT WoS článku

—