Integrating Machine Learning and IoT Technologies for Advancements in Solar Energy Systems-Reference-Cited by-同舟云学术

Integrating Machine Learning and IoT Technologies for Advancements in Solar Energy Systems

Published:2024-06-05 Issue: Volume: Page:1699-1705
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Container-title:2024 3rd International Conference on Applied Artificial Intelligence and Computing (ICAAIC)
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Author:

Venkatesan G¹,Marimuthu M²,Gomathy V³,Saranya N³,Anandaram Harishchander⁴,Arun Kumar U⁵

Affiliation:

1. CARE College of Engineering,Department of Electrical and Electronics Engineering,Tiruchirappalli,Tamilnadu,India,620009

2. Saranathan College of Engineering,Department of Electrical and Electronics Engineering,Tiruchirappalli,Tamilnadu,India,620012

3. Kathir College of Engineering,Department of Electrical and Electronics Engineering,Coimbatore,Tamilnadu,India,641062

4. Amrita Vishwa Vidyapeetham,Amrita School of Artificial Intelligence, Coimbatore,Tamil Nadu,India

5. Karpagam Academy of Higher Education (Deemed to be University),Faculty of Engineering,Department of Electrical and Electronics Engineering,Coimbatore,Tamil Nadu,India,641021

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10574858/10574894/10575346.pdf?arnumber=10575346

Reference25 articles.

1. A Two-Phase Machine Learning Approach for Predictive Maintenance of Low Voltage Industrial Motors

2. Ultra-High Speed Switched Reluctance Motor-Generator for Turbocharger Applications

3. Hybrid MPPT-Based Efficiency Improvement of Renewable Energy System Using Step-Up Converter

4. Deep learning assisted surrogate modeling of large-scale power grids

5. Ensemble learning methods using the Hodrick–Prescott filter for fault forecasting in insulators of the electrical power grids