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^*

^*Bu çalışma için yazışmadan sorumlu yazar

İnşaat Mühendisliği Bölümü

Araştırma sonucu: Kitap/Rapor/Konferans Bildirisinde Bölüm › Konferans katkısı › bilirkişi

Özet

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.

Orijinal dil	İngilizce
Ana bilgisayar yayını başlığı	Intelligent and Fuzzy Systems - Intelligent Industrial Informatics and Efficient Networks Proceedings of the INFUS 2024 Conference
Editörler	Cengiz Kahraman, Sezi Cevik Onar, Selcuk Cebi, Basar Oztaysi, Irem Ucal Sari, A. Cagrı Tolga
Yayınlayan	Springer Science and Business Media Deutschland GmbH
Sayfalar	341-348
Sayfa sayısı	8
ISBN (Basılı)	9783031700170
DOI'lar	https://doi.org/10.1007/978-3-031-70018-7_38
Yayın durumu	Yayınlandı - 2024
Etkinlik	International Conference on Intelligent and Fuzzy Systems, INFUS 2024 - Canakkale, Turkey Süre: 16 Tem 2024 → 18 Tem 2024

Yayın serisi

Adı	Lecture Notes in Networks and Systems
Hacim	1088 LNNS
ISSN (Basılı)	2367-3370
ISSN (Elektronik)	2367-3389

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???event.eventtypes.event.conference???	International Conference on Intelligent and Fuzzy Systems, INFUS 2024
Ülke/Bölge	Turkey
Şehir	Canakkale
Periyot	16/07/24 → 18/07/24

Bibliyografik not

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

Belgeye Erişim

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

Diğer Dosyalar ve Linkler

Link to publication in Scopus

Alıntı Yap

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; Hac. 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. editör / 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.",

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

author = "Alan, {Ali Rıza} and Cihan Bayındır",

note = "Publisher Copyright: {\textcopyright} The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.; International Conference on Intelligent and Fuzzy Systems, INFUS 2024 ; Conference date: 16-07-2024 Through 18-07-2024",

year = "2024",

doi = "10.1007/978-3-031-70018-7_38",

language = "English",

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series = "Lecture Notes in Networks and Systems",

publisher = "Springer Science and Business Media Deutschland GmbH",

pages = "341--348",

editor = "Cengiz Kahraman and {Cevik Onar}, Sezi and Selcuk Cebi and Basar Oztaysi and {Ucal Sari}, Irem and Tolga, {A. Cagrı}",

booktitle = "Intelligent and Fuzzy Systems - Intelligent Industrial Informatics and Efficient Networks Proceedings of the INFUS 2024 Conference",

address = "Germany",

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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, hac. 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; Hac. 1088 LNNS).

Araştırma sonucu: Kitap/Rapor/Konferans Bildirisinde Bölüm › Konferans katkısı › bilirkişi

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T1 - Spectral Analysis and Predictability of the 30 October 2020 İzmir-Samos Tsunami via ANFIS Fuzzy Network

AU - Alan, Ali Rıza

AU - Bayındır, Cihan

N1 - Publisher Copyright: © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

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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KW - İzmir-Samos (Aegean) tsunami

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BT - Intelligent and Fuzzy Systems - Intelligent Industrial Informatics and Efficient Networks Proceedings of the INFUS 2024 Conference

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A2 - Oztaysi, Basar

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PB - Springer Science and Business Media Deutschland GmbH

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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, editörler, 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