Seasonal Trend Assessment for Groundwater Contamination Detection and Monitoring using ARIMA Model-Reference-Cited by-同舟云学术

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Seasonal Trend Assessment for Groundwater Contamination Detection and Monitoring using ARIMA Model

Published:2023-02-07 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE 2nd International Conference on AI in Cybersecurity (ICAIC)
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Author:

Barajas Miguel A¹,Murphy Michael P²,Lasseter Louis C²,Sunny Godspower I²,Mazumdar Hirak²,Gohel Hardik A²,Emerson Hilary P³,Kaplan Daniel I⁴

Affiliation:

1. University Of Houston- Victoria,Department of Computer Science,Katy,Texas,USA

2. University Of Houston- Victoria,Department of Computer Science,Victoria,Texas,USA

3. Pacific Northwest National Laboratory,Richland,WA,USA

4. University of Georgia,Savannah River Ecology Lab,Aiken,SC,USA

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10044118/10044119/10044126.pdf?arnumber=10044126

Reference11 articles.

1. A Hybrid Forecasting Technique to Deal with Heteroskedastic Demand in a Supply Chain

2. On Forecasting Amazon EC2 Spot Prices Using Time-Series Decomposition with Hybrid Look-Backs

3. Trend analysis and ARIMA modelling of recent groundwater levels in the White Volta River basin of Ghana

4. Machine learning strategies for time series forecasting;bontempi;Business Intelligence,2013

5. Groundwater level prediction using machine learning models: A comprehensive review

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