Publication detail

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

CUESTA CORDOBA, G.

Original Title

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

Type

conference paper

Language

English

Original Abstract

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.

Keywords

distribution system, neural network

Authors

CUESTA CORDOBA, G.

RIV year

2011

Released

4. 2. 2011

Publisher

VUT v Brně, Fakulta stavební

Location

Brno, ČR

ISBN

978-80-214-4232-0

Book

JUNIORSTAV 2011

Edition

1

Edition number

1

Pages from

243

Pages to

253

Pages count

11

BibTex

@inproceedings{BUT36355,
  author="Gustavo Andres {Cuesta Cordoba}",
  title="Using of artificial neural network for evaluation and prediction of some drinking water quality parameters within a water distribution system",
  booktitle="JUNIORSTAV 2011",
  year="2011",
  series="1",
  number="1",
  pages="243--253",
  publisher="VUT v Brně, Fakulta stavební",
  address="Brno, ČR",
  isbn="978-80-214-4232-0"
}