KBJNet: Kinematic Bi-Joint Temporal Convolutional Network Attention for Anomaly Detection in Multivariate Time Series Data Cover

KBJNet: Kinematic Bi-Joint Temporal Convolutional Network Attention for Anomaly Detection in Multivariate Time Series Data

Data Science Journal

Volume 23 (2024): Issue 1

By: Muhammad Abdan Mulia, Muhammad Bintang Bahy, Muhammad Zain Fawwaz Nuruddin Siswantoro, Nur Rahmat Dwi Riyanto, Nella Rosa Sudianjaya and Ary Mazharuddin Shiddiqi

Open Access

|Mar 2024

Authors

Muhammad Abdan Mulia

6025222006@mhs.its.ac.id

Department of Informatics, Institut Teknologi Sepuluh Nopember, Surabaya

Muhammad Bintang Bahy

6025222003@mhs.its.ac.id

Department of Informatics, Institut Teknologi Sepuluh Nopember, Surabaya

Muhammad Zain Fawwaz Nuruddin Siswantoro

6025222009@mhs.its.ac.id

Department of Informatics, Institut Teknologi Sepuluh Nopember, Surabaya

Nur Rahmat Dwi Riyanto

6025222008@mhs.its.ac.id

Department of Informatics, Institut Teknologi Sepuluh Nopember, Surabaya

Nella Rosa Sudianjaya

6025222010@mhs.its.ac.id

Department of Informatics, Institut Teknologi Sepuluh Nopember, Surabaya

Ary Mazharuddin Shiddiqi

ary.shiddiqi@its.ac.id

Department of Informatics, Institut Teknologi Sepuluh Nopember, Surabaya

DOI: https://doi.org/10.5334/dsj-2024-010 | Journal eISSN: 1683-1470

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Language: English

Submitted on: Jun 29, 2023

Accepted on: Oct 6, 2023

Published on: Mar 4, 2024

Published by: Ubiquity Press

In partnership with: Paradigm Publishing Services

Publication frequency: 1 issue per year

Keywords:

anomaly detection,

multivariate time series data,

dilated convolution

© 2024 Muhammad Abdan Mulia, Muhammad Bintang Bahy, Muhammad Zain Fawwaz Nuruddin Siswantoro, Nur Rahmat Dwi Riyanto, Nella Rosa Sudianjaya, Ary Mazharuddin Shiddiqi, published by Ubiquity Press
This work is licensed under the Creative Commons Attribution 4.0 License.

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