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A transfer learning-based deep convolutional neural network approach for induction machine multiple faults detectionopen access

Kumar, Prashant; Hati, Ananda Shankar; Kumar, Prince

ArticleIssue Date2023CitationInternational Journal of Adaptive Control and Signal Processing, v.37, no.9, pp 2380 - 2393PublisherJohn Wiley & Sons Ltd
SCIESCOPUS
An adaptive neural fuzzy interface structure optimisation for prediction of energy consumption and airflow of a ventilation systemopen access

Prince; Hati, Ananda Shankar; Kumar, Prashant

ArticleIssue Date2023CitationApplied Energy, v.337, pp 1 - 9PublisherElsevier Ltd
SCOPUS
Bearing Fault Diagnosis in Induction Motor Using Hybrid CNN Model

Kumar, Prashant; Hati, Ananda Shankar; Prince; Kim, Heung Soo

ArticleIssue Date2024CitationLecture Notes in Mechanical Engineering, pp 411 - 418PublisherSpringer Science and Business Media Deutschland GmbH
SCIESCOPUS
Deep Transfer Learning Framework for Bearing Fault Detection in Motorsopen access

Kumar, Prashant; Kumar, Prince; Hati, Ananda Shankar; Kim, Heung Soo

ArticleIssue Date2022CitationMathematics, v.10, no.24, pp 1 - 14PublisherMDPI
SCIESCOPUS
Prediction of energy consumption and airflow of a ventilation system: A SAGA-optimised back-propagation neural network-based approachopen access

Prince; Yoon, Byungun; Hati, Ananda Shankar; Kumar, Prashant; Chakrabarti, Prasun

ArticleIssue Date2026CitationExpert Systems with Applications, v.297, pp 1 - 13PublisherElsevier Ltd
SCIESCOPUS
Residual LSTM-based short duration forecasting of polarization current for effective assessment of transformers insulationopen access

Vatsa, Aniket; Hati, Ananda Shankar; Kumar, Prashant; Margala, Martin; Chakrabarti, Prasun

ArticleIssue Date2024CitationScientific Reports, v.14, no.1PublisherNature Portfolio
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