[1] Shahpari, A.; Khansari, M.; Moeini, A. “Prediction of Vulnerability in Iran's Power Grid by Link Analysis”; J. Adv. Defence Sci. Technol. 2018, 9, 461-466.
[2] Shahidehpour, M.; Tinney, W. F.; Fu, Y. “Impact of Security on Power Systems Operation”; Proc. IEEE 2005, 11, 2013–2025. http://doi.org/10.1109/JPROC.2005.857490.
[3] Shahriyari, M.; Safari, A.; Quteishat, A.; Afsharirad, H. “A Short-Term Voltage Stability Online Assessment Based on Multi-Layer Perceptron Learning”; Electr. Pow. Syst. Res. 2023, 223, 109562. https://doi.org/10.1016/j.epsr.2023. 109562.
[4] Sayydipour, S.; Ghaffarpour, R.; Ranjbar, A. “A Review on Vulnerability Analysis of Electric Grid: Approaches, Models, and Solution Methods”; Adv. Defence Sci. & Technol. 2018, 9, 11-28. DOR: 20.1001.1.26762935. 1397.9.1.2.7
[5] Shahriyari, M.; Khoshkhoo, H. “A Novel Approach for Fast Prediction of Transient Angle Stability Status in Power Systems”; J. Adv. Defence Sci. & Technol. 2020, 3, 309-324. DOR: 20.1001.1.26762935.1399.11.3.8.1
[6] Patel, H. H.; Prajapati, P. “Study and Analysis of Decision Tree Based Classification Algorithms”; Int. J. Comp. Sci. Eng. 2018, 6, 74-78.
[7] Pal, M. “Ensemble Learning With Decision Tree for Remote Sensing Classification”; World Acad. Sci. Eng. Technol. 2007, 36, 258-260.
[8] Kalyani, S.; Swarup, K. S. “Classification and Assessment of Power System Security Using Multiclass SVM”; IEEE Trans. Syst. Man Cybernetic C., 2010, 41, 753-758. https://doi.org/10.1109/TSMCC.2010.2091630
[9] Liu, C.; Sun, K.; Rather, Z. H.; Chen, Z.; Bak, C. L.; Thøgersen, P.; Lund, P. “A Systematic Approach for Dynamic Security Assessment and The Corresponding Preventive Control Scheme Based on Decision Trees”; IEEE Trans. Power Syst. 2013, 29, 717-730. https://doi.org/ 10.1109/TPWRS.2013.2283064
[10] Zhukov, A.; Tomin, N.; Kurbatsky, V.; Sidorov, D.; Panasetsky, D.; Foley, A. “Ensemble Methods of Classification for Power Systems Security Assessment”; Appl. Applied Comput. Inform. 2019, 15, 45-53. https://doi.org/10.1016/j.aci.2017.09.007
[11] Liu, C.; Tang, F.; Leth Bak, C. “An Accurate Online Dynamic Security Assessment Scheme Based on Random Forest”; Energies 2018, 11, 1914. https://doi.org/10.3390/ en11071914
[12] Liu, J.; Sun, H.; Li, Y.; Fang, W.; Niu, S. “An Improved Power System Transient Stability Prediction Model Based on mRMR Feature Selection and WTA Ensemble Learning”; Appl. Sci. 2020, 10, 2255. https://doi.org/ 10.3390/app10072255
[13] Shahriyari, M.; Khoshkhoo, H.; Pouryekta, A.; Ramachandaramurthy, V. K. “Fast Prediction of Angle Stability Using Support Vector Machine and Fault Duration Data”; IEEE Int. Conf. Aut. Ctr. Intelligent Syst., 2019, 258-263. https://doi.org/10.1109/I2CACIS.2019.8825052
[14] Li, H.; Diao, R.; Zhang, X.; Lin, X.; Lu, X.; Shi, D.; Wang, Z.; Wang, L. “An Integrated Online Dynamic Security Assessment System for Improved Situational Awareness and Economic Operation”; IEEE Access 2019, 7, 162571-162582. https://doi.org/10.1109/ACCESS.2019.2952178.
[15] Khoshkhoo, H.; Akbarzadeh, A.P. "Prediction of Voltage Stability Status Considering the Impact of the Protection System”, J. Adv. Defence Sci. & Technol. 2021., 3, 251-263. DOR: 20.1001.1.26762935.1400.12.4.3.5
[16] Anwar, N.; Hanif, A.; Khan, H.F.; Ullah, M. F. “Transient Stability Analysis of The IEEE-9 Bus System Under Multiple Contingencies”; Eng. Technol. Appl. Sci. Res. 2020, 10, 5925-5932.
[17] Shahriyari, M.; Khoshkhoo, H. “A Deep Learning-Based Approach for Comprehensive Rotor Angle Stability Assessment”; J. Oper. Autom. Power Eng. 2022, 10, 105-112. https://doi.org/10.22098/JOAPE. 2022.8701.1607.
[18] Dietterich, T. G. “Ensemble Learning”; The handbook of brain theory and neural networks 2002, 2, 110-125.
[19] Silva-Palacios, D.; Ferri, C.; Ramírez-Quintana, M. J. “Improving Performance of Multiclass Classification by Inducing Class Hierarchies”; Procedia Comput. Sci. 2017, 108, 1692-1701. https://doi.org/10.1016/j.procs.2017. 05.218.
[20] Zhou, Z. H. “Ensemble Methods: Foundations and Algorithms”; CRC Press., 2012.
[21] Witten, I. H.; Frank, E.; Hall, M. A.; Pal, C. J.; DATA, M. “Practical Machine Learning Tools and Techniques”; Data Mining. Fourth Edition, Elsevier Publishers 2017.
[22] Bühlmann, P.; Hothorn, T. “Boosting Algorithms: Regularization, Prediction and Model Fitting”; Statist. Sci. 2007, 22, 477-505. https://doi.org/10.1214/07-STS242.
[23] Cutler, A.; Cutler, D. R.; Stevens, J. R. “Random Forests”; Ensemble Machine Learning: Methods and Applications 2012, 157-175. https://doi.org/10.1007/978-1-4419-9326-7-5
[24] Hastie, T.; Rosset, S.; Zhu, J.; Zou, H. “Multi-Class Adaboost”; Stat. Interface 2009, 2, 349-360. doi:https://dx.doi.org/10.4310/SII.2009.v2.n3.a8
[25] Zhang, S.; Zhang, C.; Yang, Q. “Data Preparation for Data Mining”; Appl. Artif. Intell. 2003, 17, 375–381. https://doi.org/10.1080/713827180.
[26] Zhang, Y.; Xu, Y.; Dong, Z. Y. “Robust Classification Model for PMU‐Based Online Power System DSA with Missing Data”; IET Gener. Transm. Dis. 2017, 11, 4484-4491. https://doi.org/10.1049/iet-gtd.2016.2010.
[27] Bachu, V.; Anuradha, J. “A Review of Feature Selection and Its Methods”; Cybernetics and Information Technologies 2019, 19(1), 3-26
[28] Al-Harbi, O. “A Comparative Study of Feature Selection Methods for Dialectal Arabic Sentiment Classification Using Support Vector Machine”; arXiv preprint arXi 1902.06242 2019. https://doi.org/10.48550/arXiv.1902. 06242.
[29] Yang, J.; Qu, Z.; Liu, Z. “Improved Feature-Selection Method Considering The Imbalance Problem in Text Categorization”; Scientific World Journal 2014, https://doi.org/10.1155/2014/625342.
[30] Sun, M.; Konstantelos, I.; Strbac, G. “A Deep Learning-Based Feature Extraction Framework for System Security Assessment”; IEEE Trans. Smart Grid 2018, 10, 5007-5020. https://doi.org/10.1109/TSG.2018.2873001.
[31] Kulkarni, A.; Chong, D.; Batarseh, F. A. “Foundations of Data Imbalance and Solutions for a Data Eemocracy”; Data democracy. Academic Press, 2020, 83-106. https://doi.org/10.1016/B978-0-12-818366-3.00005-8.
[32] Sekhar, P.; Mohanty, S. “Classification and Assessment of Power System Static Security Using Decision Tree and Random Forest Classifiers”; Int. J. Numer. Model. El. 2016 29, 465-474. https://doi.org/10.1002/jnm.2096.
[33] Zhang, T.; Sun, M.; Cremer, J. L.; Zhang, N.; Strbac, G.; Kang, C. “A Confidence-Aware Machine Learning Framework for Dynamic Security Assessment”; IEEE Trans. Power Syst., 2021, 36, 3907-3920. https://doi.org/10.1109/TPWRS.2021.3059197.
[34] Xyngi, I.; Ishchenko, A.; Popov, M.; van der Sluis, L. “Transient Stability Analysis of a Distribution Network with Distributed Generators”; IEEE Trans. Power Syst. 2009, 24, 1102-1104. https://doi.org/10.1109/TPWRS.2008.2012280.
[35] Fan, Y.; Li, X.; Zhang, P. “Integrated Approach for Online Dynamic Security Assessment with Credibility and Visualization Based on Exploring Connotative Associations in Massive Data”; IEEE Access 2017, 5, 16555-16567. https://doi.org/10.1109/ACCESS.2017.2739818.
[36] Liu, S.; Liu, L.; Fan, Y.; Zhang, L.; Huang, Y.; Zhang, T.; Cheng, J.; Wang, L.; Zhang, M.; Shi, R.; Mao, D. “An Integrated Scheme for Online Dynamic Security Assessment Based on Partial Mutual Information and Iterated Random Forest”; IEEE Trans. Smart Grid, 2020, 11, 3606-3619. https://doi.org/10.1109/TSG.2020.2991335.
[37] Mukherjee, R.; De, A. “Development of an Ensemble Decision Tree-Based Power System Dynamic Security State Predictor”; IEEE Syst. J. 2020, 14, 3836-3843. https://doi.org/10.1109/JSYST.2020.2978504.
[38] Sharma, S.; Velgapudi, N. S.; Pandey, K. “Performance Analysis of IEEE 9 Bus system using TCSC”; IEEE Recent Developments in Control, Automation & Power Engineering 2017, 251-256. https://doi.org/10.1109/RDCAPE.2017. 8358277.
[39] Shahriyari, M.; Khoshkhoo, H.; Guerrero, J. M. “A Novel Fast Transient Stability Assessment of Power Systems Using Fault-on Trajectory”; IEEE Syst. J. 2022, 16, 4334-4344. https://doi.org/10.1109/JSYST.2022.3148815.
)