Forecasting of Ra(226), Th(232) and U(238) Concentrations using Artificial Neural Networks (ANNs)

Sevim Bilici; Miraç Kamışlıoğlu; Ahmet Bilici; Fatih Külahcı

doi:10.17776/csj.359924

TR EN

Forecasting of Ra(226), Th(232) and U(238) Concentrations using Artificial Neural Networks (ANNs)

Abstract

Identification and modeling of radioactive concentrations in a region is very important for the region in terms of radiological hazards. Artificial Neural Network (ANN) can successfully model large systems. The validity of the model was tested by entering the data of the proposed ANN model that had never been entered into the system. In this research, average activity concentrations of ²²⁶Ra, ²³²Th and ²³⁸U in the water samples collected from the lake are 1.439 Bql^-1, 4.508 Bql^-1 and 14.682 Bql^-1, respectively. The characteristics of the study area are also determined with the spatial maps and ANNs are used to prediction and modeling of the radionuclides. The mean square errors for the obtained results are less than 1.5%. The correlation coefficient close to +1 indicates the validity of the model for this study.

Keywords

Natural Radioactivity,Transport,Distribution,Radium,Thorium,Uranium,Modelling,Prediction,Artificial Neural Network

References

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Details

Primary Language

English

Subjects

-

Journal Section

Conference Paper

Authors

Sevim Bilici ^*
BARTIN ÜNİVERSİTESİ
Türkiye

Miraç Kamışlıoğlu
ÜSKÜDAR ÜNİVERSİTESİ
Türkiye

Ahmet Bilici
BARTIN ÜNİVERSİTESİ
Türkiye

Fatih Külahcı
FIRAT ÜNİVERSİTESİ
Türkiye

Publication Date

March 16, 2018

Submission Date

November 30, 2017

Acceptance Date

January 31, 2018

Published in Issue

Year 2018 Volume: 39 Number: 1

DOI

https://doi.org/10.17776/csj.359924

IZ

https://izlik.org/JA75DX87NP

Cite

RIS / Bibtex

APA

Bilici, S., Kamışlıoğlu, M., Bilici, A., & Külahcı, F. (2018). Forecasting of Ra(226), Th(232) and U(238) Concentrations using Artificial Neural Networks (ANNs). Cumhuriyet Science Journal, 39(1), 87-94. https://doi.org/10.17776/csj.359924

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Forecasting of Ra(226), Th(232) and U(238) Concentrations using Artificial Neural Networks (ANNs)

Yapay Sinir Ağları (YSA) Yöntemi Kullanarak Ra-226, Th-232 ve U-238 Konsantrasyonlarının Kestirimleri

Öz

Anahtar Kelimeler

Forecasting of Ra(226), Th(232) and U(238) Concentrations using Artificial Neural Networks (ANNs)

Abstract

Keywords

References

Details

Primary Language

Subjects

Journal Section

Authors

Publication Date

Submission Date

Acceptance Date

Published in Issue

DOI

IZ

Cite

Cited By

Identification and quantification of anomalies in environmental gamma dose rate time series using artificial intelligence

Developing a Forecasting model for uranium occurrence in GII, Northeastern Desert, Egypt using artificial neural networks

Predicting the Unpredictable: Advancements in Earthquake Forecasting Using Artificial Intelligence and LSTM Networks