Spectral Analysis and Predictability of the 30 October 2020 İzmir-Samos Tsunami via ANFIS Fuzzy Network

Ali Rıza Alan; Cihan Bayındır

doi:10.1007/978-3-031-70018-7_38

Spectral Analysis and Predictability of the 30 October 2020 İzmir-Samos Tsunami via ANFIS Fuzzy Network

Ali Rıza Alan
, Cihan Bayındır^*

^*Corresponding author for this work

Department of Civil Engineering

Istanbul Technical University
Bogazici University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

In this study, we analyze the spectral and time series features of the 30 October 2020 İzmir-Samos (Aegean) tsunami by fuzzy time series analysis approach. To be more precise, we examine the 30 October 2020 İzmir-Samos tsunami time series data that is obtained from the UNESCO data portal and we examine the application and limitations of the Adaptive Neuro-Fuzzy Inference System (ANFIS) fuzzy network approach for the prediction of the time series and spectra of tsunami data acquired. In particular, we examine the predictability of the dynamics of water surface elevations recorded at two stations, namely the Bodrum and the Kos station during the 30 October 2020 İzmir-Samos (Aegean) tsunami event. We also investigate the aforementioned event’s spectral features: frequency and amplitude properties using the ANFIS fuzzy network. We provide an analysis of our results and discuss their possible applications and potential future uses. Our findings are promising for the prediction and analysis of tsunami hydrodynamics by the fuzzy networks.

Original language	English
Title of host publication	Intelligent and Fuzzy Systems - Intelligent Industrial Informatics and Efficient Networks Proceedings of the INFUS 2024 Conference
Editors	Cengiz Kahraman, Sezi Cevik Onar, Selcuk Cebi, Basar Oztaysi, Irem Ucal Sari, A. Cagrı Tolga
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	341-348
Number of pages	8
ISBN (Print)	9783031700170
DOIs	https://doi.org/10.1007/978-3-031-70018-7_38
Publication status	Published - 2024
Event	International Conference on Intelligent and Fuzzy Systems, INFUS 2024 - Canakkale, Turkey Duration: 16 Jul 2024 → 18 Jul 2024

Publication series

Name	Lecture Notes in Networks and Systems
Volume	1088 LNNS
ISSN (Print)	2367-3370
ISSN (Electronic)	2367-3389

Conference

Conference	International Conference on Intelligent and Fuzzy Systems, INFUS 2024
Country/Territory	Turkey
City	Canakkale
Period	16/07/24 → 18/07/24

Bibliographical note

Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

Keywords

ANFIS
Fuzzy network
Spectral and time series analysis & prediction
İzmir-Samos (Aegean) tsunami

Access to Document

10.1007/978-3-031-70018-7_38

Cite this

Alan, A. R., & Bayındır, C. (2024). Spectral Analysis and Predictability of the 30 October 2020 İzmir-Samos Tsunami via ANFIS Fuzzy Network. In C. Kahraman, S. Cevik Onar, S. Cebi, B. Oztaysi, I. Ucal Sari, & A. C. Tolga (Eds.), Intelligent and Fuzzy Systems - Intelligent Industrial Informatics and Efficient Networks Proceedings of the INFUS 2024 Conference (pp. 341-348). (Lecture Notes in Networks and Systems; Vol. 1088 LNNS). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-70018-7_38

Alan, Ali Rıza ; Bayındır, Cihan. / Spectral Analysis and Predictability of the 30 October 2020 İzmir-Samos Tsunami via ANFIS Fuzzy Network. Intelligent and Fuzzy Systems - Intelligent Industrial Informatics and Efficient Networks Proceedings of the INFUS 2024 Conference. editor / Cengiz Kahraman ; Sezi Cevik Onar ; Selcuk Cebi ; Basar Oztaysi ; Irem Ucal Sari ; A. Cagrı Tolga. Springer Science and Business Media Deutschland GmbH, 2024. pp. 341-348 (Lecture Notes in Networks and Systems).

@inproceedings{191f5c97af9041d8b37a8f737725baf4,

title = "Spectral Analysis and Predictability of the 30 October 2020 İzmir-Samos Tsunami via ANFIS Fuzzy Network",

abstract = "In this study, we analyze the spectral and time series features of the 30 October 2020 İzmir-Samos (Aegean) tsunami by fuzzy time series analysis approach. To be more precise, we examine the 30 October 2020 İzmir-Samos tsunami time series data that is obtained from the UNESCO data portal and we examine the application and limitations of the Adaptive Neuro-Fuzzy Inference System (ANFIS) fuzzy network approach for the prediction of the time series and spectra of tsunami data acquired. In particular, we examine the predictability of the dynamics of water surface elevations recorded at two stations, namely the Bodrum and the Kos station during the 30 October 2020 İzmir-Samos (Aegean) tsunami event. We also investigate the aforementioned event{\textquoteright}s spectral features: frequency and amplitude properties using the ANFIS fuzzy network. We provide an analysis of our results and discuss their possible applications and potential future uses. Our findings are promising for the prediction and analysis of tsunami hydrodynamics by the fuzzy networks.",

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Alan, AR & Bayındır, C 2024, Spectral Analysis and Predictability of the 30 October 2020 İzmir-Samos Tsunami via ANFIS Fuzzy Network. in C Kahraman, S Cevik Onar, S Cebi, B Oztaysi, I Ucal Sari & AC Tolga (eds), Intelligent and Fuzzy Systems - Intelligent Industrial Informatics and Efficient Networks Proceedings of the INFUS 2024 Conference. Lecture Notes in Networks and Systems, vol. 1088 LNNS, Springer Science and Business Media Deutschland GmbH, pp. 341-348, International Conference on Intelligent and Fuzzy Systems, INFUS 2024, Canakkale, Turkey, 16/07/24. https://doi.org/10.1007/978-3-031-70018-7_38

Spectral Analysis and Predictability of the 30 October 2020 İzmir-Samos Tsunami via ANFIS Fuzzy Network. / Alan, Ali Rıza; Bayındır, Cihan.
Intelligent and Fuzzy Systems - Intelligent Industrial Informatics and Efficient Networks Proceedings of the INFUS 2024 Conference. ed. / Cengiz Kahraman; Sezi Cevik Onar; Selcuk Cebi; Basar Oztaysi; Irem Ucal Sari; A. Cagrı Tolga. Springer Science and Business Media Deutschland GmbH, 2024. p. 341-348 (Lecture Notes in Networks and Systems; Vol. 1088 LNNS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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PY - 2024

Y1 - 2024

N2 - In this study, we analyze the spectral and time series features of the 30 October 2020 İzmir-Samos (Aegean) tsunami by fuzzy time series analysis approach. To be more precise, we examine the 30 October 2020 İzmir-Samos tsunami time series data that is obtained from the UNESCO data portal and we examine the application and limitations of the Adaptive Neuro-Fuzzy Inference System (ANFIS) fuzzy network approach for the prediction of the time series and spectra of tsunami data acquired. In particular, we examine the predictability of the dynamics of water surface elevations recorded at two stations, namely the Bodrum and the Kos station during the 30 October 2020 İzmir-Samos (Aegean) tsunami event. We also investigate the aforementioned event’s spectral features: frequency and amplitude properties using the ANFIS fuzzy network. We provide an analysis of our results and discuss their possible applications and potential future uses. Our findings are promising for the prediction and analysis of tsunami hydrodynamics by the fuzzy networks.

AB - In this study, we analyze the spectral and time series features of the 30 October 2020 İzmir-Samos (Aegean) tsunami by fuzzy time series analysis approach. To be more precise, we examine the 30 October 2020 İzmir-Samos tsunami time series data that is obtained from the UNESCO data portal and we examine the application and limitations of the Adaptive Neuro-Fuzzy Inference System (ANFIS) fuzzy network approach for the prediction of the time series and spectra of tsunami data acquired. In particular, we examine the predictability of the dynamics of water surface elevations recorded at two stations, namely the Bodrum and the Kos station during the 30 October 2020 İzmir-Samos (Aegean) tsunami event. We also investigate the aforementioned event’s spectral features: frequency and amplitude properties using the ANFIS fuzzy network. We provide an analysis of our results and discuss their possible applications and potential future uses. Our findings are promising for the prediction and analysis of tsunami hydrodynamics by the fuzzy networks.

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A2 - Oztaysi, Basar

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Alan AR, Bayındır C. Spectral Analysis and Predictability of the 30 October 2020 İzmir-Samos Tsunami via ANFIS Fuzzy Network. In Kahraman C, Cevik Onar S, Cebi S, Oztaysi B, Ucal Sari I, Tolga AC, editors, Intelligent and Fuzzy Systems - Intelligent Industrial Informatics and Efficient Networks Proceedings of the INFUS 2024 Conference. Springer Science and Business Media Deutschland GmbH. 2024. p. 341-348. (Lecture Notes in Networks and Systems). doi: 10.1007/978-3-031-70018-7_38