Alan Nesbitt

Mr.

Head of Department, Department of Electrical and Electronic Engineering

https://orcid.org/0000-0003-3518-7656

Emailane2@gcu.ac.uk

70 Cowcaddens Road, Glasgow Caledonian University
G4 0BA Glasgow
United Kingdom

Research output per year

If you made any changes in Pure these will be visible here soon.

Fingerprint

Dive into the research topics where Alan Nesbitt is active. These topic labels come from the works of this person. Together they form a unique fingerprint.

11 Similar Profiles

Network

Recent external collaboration on country level. Dive into details by clicking on the dots.

14 Conference contribution
6 Article

1D-CNN based real-time fault detection system for power asset diagnostics
Mitiche, I., Nesbitt, A., Conner, S., Boreham, P. & Morison, G., 1 Dec 2020, In: IET Generation, Transmission & Distribution. 14, 24, p. 5766-5773 8 p.
Research output: Contribution to journal › Article › peer-review

Open Access
File
119 Downloads (Pure)
Low complexity classification of power asset faults for real time IoT-based diagnostics
Salimy, A., Mitiche, I., Boreham, P., Nesbitt, A. & Morison, G., 2 Oct 2020, (Accepted/In press) Proceedings of 2020 IEEE Global Conference on Artificial Intelligence and Internet of Things. IEEE
Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Open Access
File
6 Downloads (Pure)
Deep complex neural network learning for high-voltage insulation fault classification from complex bispectrum representation
Mitiche, I., Jenkins, M. D., Boreham, P., Nesbitt, A. & Morison, G., 18 Nov 2019, 2019 27th European Signal Processing Conference (EUSIPCO). IEEE, 5 p.
Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Open Access
File
85 Downloads (Pure)
Naive bayes multi-label classification approach for high-voltage condition monitoring
Mitiche, I., Nesbitt, A., Boreham, P., Stewart, B. G. & Morison, G., 7 Jan 2019, 2018 IEEE International Conference on Internet of Things and Intelligence System (IOTAIS). IEEE, p. 162-166 5 p.
Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Open Access
File
71 Downloads (Pure)
Classification of EMI discharge sources using time–frequency features and multi-class support vector machine
Mitiche, I., Morison, G., Nesbitt, A., Hughes-Narborough, M., Stewart, B. G. & Boreham, P., Oct 2018, In: Electric Power Systems Research. 163, Part A, p. 261-269 9 p.
Research output: Contribution to journal › Article › peer-review

Open Access
File
61 Downloads (Pure)

1D-CNN based real-time fault detection system for power asset diagnostics

Low complexity classification of power asset faults for real time IoT-based diagnostics

Deep complex neural network learning for high-voltage insulation fault classification from complex bispectrum representation

Naive bayes multi-label classification approach for high-voltage condition monitoring

Classification of EMI discharge sources using time–frequency features and multi-class support vector machine