Iroshani Jayawardene
Orcid: 0000-0002-8297-9763Affiliations:
- Clemson University, SC, USA
According to our database1,
Iroshani Jayawardene
authored at least 12 papers
between 2014 and 2024.
Collaborative distances:
Collaborative distances:
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Bibliography
2024
Towards an Open Energy Management System for Integrated Energy Storage and Electric Vehicle Fast Charging Station.
Proceedings of the Companion Proceedings of the 8th International Joint Conference on Rules and Reasoning co-located with 20th Reasoning Web Summer School (RW 2024) and 16th DecisionCAMP 2024 as part of Declarative AI 2024, 2024
Proceedings of the Companion Proceedings of the 8th International Joint Conference on Rules and Reasoning co-located with 20th Reasoning Web Summer School (RW 2024) and 16th DecisionCAMP 2024 as part of Declarative AI 2024, 2024
2022
Resilient and Sustainable Tie-Line Bias Control for a Power System in Uncertain Environments.
IEEE Trans. Emerg. Top. Comput. Intell., 2022
2020
Proceedings of the 2020 International Joint Conference on Neural Networks, 2020
2018
CI-based Analytics for Photovoltaic Power Predictions and Tie-line Bias Control in Smart Grid.
Proceedings of the IEEE Symposium Series on Computational Intelligence, 2018
2017
IEEE Trans. Emerg. Top. Comput. Intell., 2017
Optimized automatic generation control in a multi-area power system with particle swarm optimization.
Proceedings of the 2017 IEEE Symposium Series on Computational Intelligence, 2017
Cellular computational extreme learning machine network based frequency predictions in a power system.
Proceedings of the 2017 International Joint Conference on Neural Networks, 2017
2015
Reservoir based learning network for control of two-area power system with variable renewable generation.
Neurocomputing, 2015
Frequency Prediction of Synchronous Generators in a Multi-Machine Power System with a Photovoltaic Plant Using a Cellular Computational Network.
Proceedings of the IEEE Symposium Series on Computational Intelligence, 2015
Comparison of Adaptive Neuro-Fuzzy Inference Systems and Echo State Networks for PV Power Prediction.
Proceedings of the INNS Conference on Big Data 2015, 2015
2014
Comparison of echo state network and extreme learning machine for PV power prediction.
Proceedings of the 2014 IEEE Symposium on Computational Intelligence Applications in Smart Grid, 2014