Publication detail

Neural network for waste-water recognition

KUCHTA, R., VRBA, R., FUJCIK, L.

Original Title

Neural network for waste-water recognition

English Title

Neural network for waste-water recognition

Type

conference paper

Language

en

Original Abstract

This paper presents neural network for waste-water recognition by using sensor array. Each sensor in sensor array detects chemicals in waste-water with different sensitivity. Set of measured data is digitized and recognized by a neural network. Measuring process doesn’t need any human operator. The result gives the only information: contaminated or not contaminated.

English abstract

This paper presents neural network for waste-water recognition by using sensor array. Each sensor in sensor array detects chemicals in waste-water with different sensitivity. Set of measured data is digitized and recognized by a neural network. Measuring process doesn’t need any human operator. The result gives the only information: contaminated or not contaminated.

Keywords

Neural network, waste-water, sensor array, contaminated water, sewerage plant.

RIV year

2004

Released

01.01.2004

Publisher

WSEAS

Location

Rio de Janeiro

ISBN

960-8457-03-3

Book

Proceedings of the WSEAS Conferences, Rio de Janeiro, Brasil 2004

Edition number

1

Pages from

223

Pages to

225

Pages count

3

BibTex


@inproceedings{BUT11929,
  author="Radek {Kuchta} and Radimír {Vrba} and Lukáš {Fujcik}",
  title="Neural network for waste-water recognition",
  annote="This paper presents neural network for waste-water recognition by using sensor array. Each sensor in sensor
array detects chemicals in waste-water with different sensitivity. Set of measured data is digitized and recognized by a
neural network. Measuring process doesn’t need any human operator. The result gives the only information:
contaminated or not contaminated.",
  address="WSEAS",
  booktitle="Proceedings of the WSEAS Conferences, Rio de Janeiro, Brasil 2004",
  chapter="11929",
  institution="WSEAS",
  year="2004",
  month="january",
  pages="223",
  publisher="WSEAS",
  type="conference paper"
}