EVALUATION OF WATER QUALITY THROUGH ARTIFICIAL NEURAL NETWORKS

Year 2017, Volume: Volume 2 Issue: İssue 1 (1) - 2.İnternational Congress Of Forensic Toxicology, 180 - 180, 16.02.2017

Semra Benzer , Recep Benzer

https://izlik.org/JA82EC23GY

Abstract

Increasing human
pressure on water resources has led to the problem of water pullution. Thus,
the determination and the evaluation of the quality of water resources should
be dealth with scientific studies. 
Knowledge of the potential risks in quantity and quality of water reveal
the necessity of regular control and monitoring which can be achieved through
long term data collection and the organization of a common database.

In the
determination of the surface water quality; organic, inorganic, radiological,
bacteriological parameters are important parameters. Among these parameters,
the physico- chemical parameters of water quality are used in this study. To
determine the change in physico- chemical parameters in Yeşilırmak - Duruca,
Yeşilırmak – Çayköy and Tersakan Stream – Boğazköy stations, a new approach
based on Artificial Neural Networks (ANN) is used. It is a forecasting
application used in several fields. The predetermined physico-chemical
parameters of Amasya Provincial Directorate of Agriculture were used for the
forecasting process which indicated a possible significant danger in water
quality at the mentioned stations and a requirement for the necessary
measurements. Our country is in a critical region in terms of water resources,
the determination of the status of water resources, it is important to conduct
a lot of research for the development and preservation. For this purpose,
quality monitoring stations in the measured parameters, be managed in a common
database, the creation of a national water quality monitoring network making
long-term data collection is required.

Eventually, the
techniques of ANN can be utilized to similar studies for different areas with
big data collected properly.

Keywords

EVALUATION OF WATER QUALITY THROUGH ARTIFICIAL NEURAL NETWORKS

References

• Semra BENZER, Recep BENZER
• Gazi University, Gazi Faculty of Education, Department of Science Education, Ankara, Turkey Gazi University, Institute of Information, Department of Forensics Computing Ankara, Turkey