9 citations to 10.1109/IYCE.2015.7180828 (Crossref Cited-By Service)

1. Michael Negnevitsky, Nikita Tomin, Victor Kurbatsky, Daniil Panasetsky, Alexey Zhukov, Christian Rehtanz, 2015 IEEE Eindhoven PowerTech, 2015, 1  
2. Peyman Razmi, Mahdi Ghaemi Asl, Application of Machine Learning and Deep Learning Methods to Power System Problems, 2021, 357  
3. Rishav Baishya, Rajib Sarkar, “A neural network-based approach for prediction of PGA and significant duration parameters in the Uttarakhand region of India”, Environ Earth Sci, 81, no. 13, 2022, 342  
4. Walter M. Villa-Acevedo, Jesús M. López-Lezama, Delia G. Colomé, Jaime Cepeda, “Long-term voltage stability monitoring of power system areas using a kernel extreme learning machine approach”, Alexandria Engineering Journal, 61, no. 2, 2022, 1353  
5. Milad Dalali, Hossein Kazemi Karegar, “Voltage instability prediction based on reactive power reserve of generating units and zone selection”, IET Generation, Transmission & Distribution, 13, no. 8, 2019, 1432  
6. Yu Zhang, Xiaohui Song, Yong Li, Zilong Zeng, Chenchen Yong, Denis Sidorov, Xia Lv, “Two-Stage Active and Reactive Power Coordinated Optimal Dispatch for Active Distribution Network Considering Load Flexibility”, Energies, 13, no. 22, 2020, 5922  
7. N. Tomin, A. Zhukov, V. Kurbatsky, D. Sidorov, M. Negnevitsky, 2017 IEEE Manchester PowerTech, 2017, 1  
8. Walter M. Villa-Acevedo, Jesús M. López-Lezama, Delia G. Colomé, “Voltage Stability Margin Index Estimation Using a Hybrid Kernel Extreme Learning Machine Approach”, Energies, 13, no. 4, 2020, 857  
9. Sen Wang, Yonghui Sun, Yan Zhou, Rabea Jamil Mahfoud, Dongchen Hou, “A New Hybrid Short-Term Interval Forecasting of PV Output Power Based on EEMD-SE-RVM”, Energies, 13, no. 1, 2019, 87