Adversarial Semi-Supervised Learning for Diagnosing Faults and Attacks in Power Grids

Autor: Roozbeh Razavi-Far, Mehrdad Saif, Ehsan Hallaji, Masood Parvania, Maryam Farajzadeh-Zanjani

Publikováno v: Electrical and Computer Engineering Publications

This paper proposes a novel adversarial scheme for learning from data under harsh learning conditions of partially labelled samples and skewed class distributions. This novel scheme integrates the generative ability of the state-of-the-art conditiona

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::91cdb907f0fb4677ed48f7ba51ad0518
https://doi.org/10.1109/tsg.2021.3061395

Generative Adversarial Networks: A Survey on Training, Variants, and Applications

Autor: Maryam Farajzadeh-Zanjani, Roozbeh Razavi-Far, Mehrdad Saif, Vasile Palade

Publikováno v: Electrical and Computer Engineering Publications
Intelligent Systems Reference Library ISBN: 9783030913892

In recent years, Generative Adversarial Network (GAN) and its variants have gained great popularity in both academia and industry. In this chapter, we survey different state-of-the-art GAN-based methods and their applications. These techniques vary i

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::655512e569ab10df1f7a3f12c2ed7b25
https://scholar.uwindsor.ca/electricalengpub/75

Generative adversarial dimensionality reduction for diagnosing faults and attacks in cyber-physical systems

Autor: Ehsan Hallaji, Maryam Farajzadeh-Zanjani, Mehrdad Saif, Roozbeh Razavi-Far

Publikováno v: Electrical and Computer Engineering Publications

In cyber-physical systems, transforming a large amount of data collected from various sensors onto informative low-dimension data is of paramount importance for efficient monitoring and safe and secure operation of the system. To this aim, this paper

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::bdecb089d1c07505527b524586a00281
https://scholar.uwindsor.ca/electricalengpub/89

An Integrated Class-Imbalanced Learning Scheme for Diagnosing Bearing Defects in Induction Motors

Autor: Maryam Farajzadeh-Zanjani, Roozbeh Razavi-Far, Mehrdad Saif

Publikováno v: Electrical and Computer Engineering Publications

This paper focuses on the development of an integrated scheme for diagnosing bearing defects in induction motors, under the class-imbalanced condition. This scheme comprises of four main modules: segmentation, feature extraction, feature reduction, a

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::45ab17fc0b4c4612982bb377235bc19f
https://doi.org/10.1109/tii.2017.2755064

Information Fusion and Semi-Supervised Deep Learning Scheme for Diagnosing Gear Faults in Induction Machine Systems

Autor: Mehrdad Saif, Maryam Farajzadeh-Zanjani, Gerard-Andre Capolino, Ehsan Hallaji, Humberto Henao, Roozbeh Razavi-Far, Shahin Hedayati Kia

Publikováno v: IEEE Transactions on Industrial Electronics
IEEE Transactions on Industrial Electronics, Institute of Electrical and Electronics Engineers, 2019, 66 (8), pp.6331-6342. ⟨10.1109/TIE.2018.2873546⟩
Electrical and Computer Engineering Publications

There has been an increasing interest in the design of intelligent diagnostic systems for industrial applications. The key requirement in the design of practical diagnostic systems is the ability for decision making in high-dimensional feature spaces

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::03b64a5c9f7cd8d5082e9fd25852690f
https://hal.archives-ouvertes.fr/hal-03116790