About: Using of artificial neural network for evaluation and prediction of some drinking water quality parameters within a water distribution system     Goto   Sponge   NotDistinct   Permalink

An Entity of Type : http://linked.opendata.cz/ontology/domain/vavai/Vysledek, within Data Space : linked.opendata.cz associated with source document(s)

AttributesValues
rdf:type
Description
  • 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.
  • 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. (en)
Title
  • Using of artificial neural network for evaluation and prediction of some drinking water quality parameters within a water distribution system
  • Using of artificial neural network for evaluation and prediction of some drinking water quality parameters within a water distribution system (en)
skos:prefLabel
  • Using of artificial neural network for evaluation and prediction of some drinking water quality parameters within a water distribution system
  • Using of artificial neural network for evaluation and prediction of some drinking water quality parameters within a water distribution system (en)
skos:notation
  • RIV/00216305:26110/11:PU91296!RIV12-MSM-26110___
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • S
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
  • Cuesta Cordoba, Gustavo Andres
http://linked.open.../riv/druhVysledku
http://linked.open...iv/duvernostUdaju
http://linked.open...titaPredkladatele
http://linked.open...dnocenehoVysledku
  • 237373
http://linked.open...ai/riv/idVysledku
  • RIV/00216305:26110/11:PU91296
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • distribution system, neural network (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [C71C23D3E929]
http://linked.open...v/mistoKonaniAkce
  • Brno
http://linked.open...i/riv/mistoVydani
  • Brno, ČR
http://linked.open...i/riv/nazevZdroje
  • JUNIORSTAV 2011
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...UplatneniVysledku
http://linked.open...iv/tvurceVysledku
  • Cuesta Cordoba, Gustavo Andres
http://linked.open...vavai/riv/typAkce
http://linked.open.../riv/zahajeniAkce
number of pages
http://purl.org/ne...btex#hasPublisher
  • Vysoké učení technické v Brně. Fakulta stavební
https://schema.org/isbn
  • 978-80-214-4232-0
http://localhost/t...ganizacniJednotka
  • 26110
Faceted Search & Find service v1.16.118 as of Jun 21 2024


Alternative Linked Data Documents: ODE     Content Formats:   [cxml] [csv]     RDF   [text] [turtle] [ld+json] [rdf+json] [rdf+xml]     ODATA   [atom+xml] [odata+json]     Microdata   [microdata+json] [html]    About   
This material is Open Knowledge   W3C Semantic Web Technology [RDF Data] Valid XHTML + RDFa
OpenLink Virtuoso version 07.20.3240 as of Jun 21 2024, on Linux (x86_64-pc-linux-gnu), Single-Server Edition (126 GB total memory, 48 GB memory in use)
Data on this page belongs to its respective rights holders.
Virtuoso Faceted Browser Copyright © 2009-2024 OpenLink Software