Proceedings of the 1st International Conference on Neural Networks and Machine Learning 2022 (ICONNSMAL 2022)

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Application of Spatial Temporal Graph Neural Networks for Forecasting Data Time Series River Pollution Waste Content in Probolinggo

Authors
Nur Mauliska1, Wahyu Lestari1, *, Endah Tri Wisudaningsih2, Muhammad Hifdil Islam2
1Department of Mathematics Education, Zainul Hasan Genggong Islamic University, Probolinggo, Indonesia
2Departement of Islamic Religious Education, Zainul Hasan Genggong Islamic University, Probolinggo, Indonesia
*Corresponding author. Email: why.lestari94@gmail.com
Corresponding Author
Wahyu Lestari
Available Online 22 May 2023.
DOI
10.2991/978-94-6463-174-6_19How to use a DOI?
Keywords
SRAC; STGNN; Artificial Neural Networks; River Waste Time Series Analysis
Abstract

Flooding has become a serious problem in Probolinggo. One of the causes of flooding is the accumulation of garbage in the river. Garbage can also cause river water pollution. To measure water pollution, we use a pH meter. SRAC (Strong Rainbow Antimagic Coloring) is the smallest number of colors taken from all rainbow colorings and is induced by strong antimagic rainbow labeling from G. The coloring resulting from SRAC determine the placement of river waste cleaner. In this study we apply spatial temporal graph neural networks (STGNN) to predict river waste in the future. In this study, the best error value is 3.2262 × 10 - 6 which is generated using a weight of 0.1 and 12 iterations. Based on the test results, the smalest MSE 5.0687 × 10 - 9 , obtained from ANN model Cascadeforwardnet with 468 architectures.

Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 1st International Conference on Neural Networks and Machine Learning 2022 (ICONNSMAL 2022)
Series
Advances in Intelligent Systems Research
Publication Date
22 May 2023
ISBN
978-94-6463-174-6
ISSN
1951-6851
DOI
10.2991/978-94-6463-174-6_19How to use a DOI?
Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Nur Mauliska
AU  - Wahyu Lestari
AU  - Endah Tri Wisudaningsih
AU  - Muhammad Hifdil Islam
PY  - 2023
DA  - 2023/05/22
TI  - Application of Spatial Temporal Graph Neural Networks for Forecasting Data Time Series River Pollution Waste Content in Probolinggo
BT  - Proceedings of the 1st International Conference on Neural Networks and Machine Learning 2022 (ICONNSMAL 2022)
PB  - Atlantis Press
SP  - 257
EP  - 272
SN  - 1951-6851
UR  - https://doi.org/10.2991/978-94-6463-174-6_19
DO  - 10.2991/978-94-6463-174-6_19
ID  - Mauliska2023
ER  -