{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,2]],"date-time":"2026-05-02T01:35:44Z","timestamp":1777685744787,"version":"3.51.4"},"reference-count":114,"publisher":"SAGE Publications","issue":"3","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["HIS"],"published-print":{"date-parts":[[2024,9,19]]},"abstract":"<jats:p>The optimal functioning of the power system is crucially dependent upon the sound protection of its major stakeholder, i.e., the transmission line, as it is prone to fault. To\u00a0maintain the integrity of the power system and protect costly power system equipment, protective relaying is necessary to provide a steady and affordable supply of electricity. Relays recognize, classify, and identify transmission line faults using input signals of voltage and current. Many artificial intelligent methods based on Expert Systems, Artificial Neural Networks, Fuzzy Logic, Support Vector Machines, Wavelet-based systems, and deep learning techniques are being investigated to improve modern digital relays\u2019 consistency, speed, and accuracy. This paper is a comprehensive and all-inclusive survey that reviews and incorporates Phasor Measurement Unit (PMU) and Global Positioning System (GPS) approaches together with all of these intelligent transmission line safety strategies and concepts. Initial investigators will benefit from this study by being able to examine, evaluate, and analyze\u00a0a variety of approaches with references for all relevant contributions.<\/jats:p>","DOI":"10.3233\/his-240016","type":"journal-article","created":{"date-parts":[[2024,6,28]],"date-time":"2024-06-28T13:38:46Z","timestamp":1719581926000},"page":"185-206","source":"Crossref","is-referenced-by-count":1,"title":["Role of artificial intelligence in transmission line protection: A review of three decades of research"],"prefix":"10.1177","volume":"20","author":[{"given":"Yajnaseni","family":"Dash","sequence":"first","affiliation":[{"name":"School of Artificial Intelligence, Bennett University, Greater Noida, U.P., India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ajith","family":"Abraham","sequence":"additional","affiliation":[{"name":"School of Artificial Intelligence, Bennett University, Greater Noida, U.P., India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Naween","family":"Kumar","sequence":"additional","affiliation":[{"name":"School of Computer Science Engineering and Technology, Bennett University, Greater Noida, U.P., India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Manish","family":"Raj","sequence":"additional","affiliation":[{"name":"School of Computer Science Engineering and Technology, Bennett University, Greater Noida, U.P., India"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"179","reference":[{"issue":"1","key":"10.3233\/HIS-240016_ref1","doi-asserted-by":"crossref","first-page":"21","DOI":"10.1049\/hve.2017.0131","article-title":"State-of-the-art on the protection of facts compensated high-voltage transmission lines: a review","volume":"3","author":"Biswas","year":"2018","journal-title":"High Voltage"},{"key":"10.3233\/HIS-240016_ref2","first-page":"1","article-title":"Transmission line protection philosophy","author":"Patel","year":"2021","journal-title":"Futuristic Trends in Numerical Relaying for Transmission Line Protections"},{"key":"10.3233\/HIS-240016_ref3","doi-asserted-by":"crossref","unstructured":"P.M. Anderson, C.F. Henville, R. Rifaat, B. Johnson and S. Meliopoulos, Power System Protection, John Wiley and Sons (2022).","DOI":"10.1002\/9781119513100"},{"issue":"7","key":"10.3233\/HIS-240016_ref4","doi-asserted-by":"crossref","first-page":"5799","DOI":"10.1007\/s10462-022-10296-0","article-title":"Application of machine learning methods in fault detection and classification of power transmission lines: a survey","volume":"56","author":"Shakiba","year":"2023","journal-title":"Artificial Intelligence Review"},{"issue":"1","key":"10.3233\/HIS-240016_ref5","doi-asserted-by":"crossref","first-page":"809","DOI":"10.3390\/su15010809","article-title":"Two terminal instantaneous power-based fault classification and location techniques for transmission lines","volume":"15","author":"Muzzammel","year":"2023","journal-title":"Sustainability"},{"key":"10.3233\/HIS-240016_ref6","first-page":"131","article-title":"Principles of high-speed relaying","volume":"3","author":"Lewis","year":"1943","journal-title":"Westinghouse Engineer"},{"key":"10.3233\/HIS-240016_ref7","doi-asserted-by":"crossref","unstructured":"E.W. Kimbark, Power System Stability, John Wiley and Sons 1 (1995).","DOI":"10.1109\/MPER.1995.365076"},{"key":"10.3233\/HIS-240016_ref8","doi-asserted-by":"crossref","unstructured":"A.G. Phadke and J.S. Thorp, Computer Relaying for Power Systems, John Wiley and Sons (2009).","DOI":"10.1002\/9780470749722"},{"key":"10.3233\/HIS-240016_ref9","doi-asserted-by":"crossref","unstructured":"A. Yadav and Y. Dash, An overview of transmission line protection by artificial neural network: fault detection, fault classification, fault location, and fault direction discrimination, Advances in Artificial Neural Systems (2014).","DOI":"10.1155\/2014\/230382"},{"key":"10.3233\/HIS-240016_ref10","doi-asserted-by":"crossref","first-page":"108622","DOI":"10.1016\/j.ijepes.2022.108622","article-title":"A novel deep learning\u2013based fault diagnosis algorithm for preventing protection malfunction","volume":"144","author":"Hu","year":"2023","journal-title":"International Journal of Electrical Power and Energy Systems"},{"issue":"4","key":"10.3233\/HIS-240016_ref11","doi-asserted-by":"crossref","first-page":"2057","DOI":"10.1080\/03772063.2021.1886601","article-title":"Fault detection and classification scheme for transmission lines connecting windfarm using single end impedance","volume":"69","author":"Paul","year":"2023","journal-title":"IETE Journal of Research"},{"issue":"1","key":"10.3233\/HIS-240016_ref12","doi-asserted-by":"crossref","first-page":"137","DOI":"10.3390\/signals4010007","article-title":"The use of instantaneous overcurrent relay in determining the threshold current and voltage for optimal fault protection and control in transmission line","volume":"4","author":"Ogar","year":"2023","journal-title":"Signals"},{"key":"10.3233\/HIS-240016_ref13","doi-asserted-by":"crossref","first-page":"108952","DOI":"10.1016\/j.ijepes.2023.108952","article-title":"Fault current control of mmc in hvdc-connected offshore wind farm: A coordinated perspective with current differential protection","volume":"148","author":"Gao","year":"2023","journal-title":"International Journal of Electrical Power and Energy Systems"},{"issue":"2","key":"10.3233\/HIS-240016_ref14","first-page":"123","article-title":"Differential protection of ispst using chebyshev neural network","volume":"11","author":"Bhasker","year":"2023","journal-title":"Journal of Operation and Automation in Power Engineering"},{"key":"10.3233\/HIS-240016_ref15","unstructured":"G. Ziegler, Numerical Distance Protection: Principles and Applications, John Wiley and Sons (2011)."},{"key":"10.3233\/HIS-240016_ref16","doi-asserted-by":"crossref","first-page":"438","DOI":"10.1109\/TPAS.1969.292466","article-title":"Fault protection with a digital computer","volume":"4","author":"Rockefeller","year":"1969","journal-title":"IEEE Transactions on Power Apparatus and Systems"},{"key":"10.3233\/HIS-240016_ref17","doi-asserted-by":"crossref","first-page":"1235","DOI":"10.1109\/TPAS.1972.293482","article-title":"High-speed distance relaying using a digital computer i-system description","volume":"3","author":"Gilcrest","year":"1972","journal-title":"IEEE Transactions on Power Apparatus and Systems"},{"key":"10.3233\/HIS-240016_ref18","doi-asserted-by":"crossref","first-page":"1244","DOI":"10.1109\/TPAS.1972.293483","article-title":"High-speed distance relaying using a digital computer ii-test results","volume":"3","author":"Rockefeller","year":"1972","journal-title":"IEEE Transactions on Power Apparatus and Systems"},{"key":"10.3233\/HIS-240016_ref19","unstructured":"M. Sachdev et al., Computer relaying, IEEE tutorial course text 79 (1979)."},{"issue":"2","key":"10.3233\/HIS-240016_ref20","doi-asserted-by":"crossref","first-page":"859","DOI":"10.1109\/TPWRD.2007.893596","article-title":"Transmission line boundary protection using wavelet transform and neural network","volume":"22","author":"Zhang","year":"2007","journal-title":"IEEE Transactions on Power Delivery"},{"key":"10.3233\/HIS-240016_ref21","first-page":"1","article-title":"Advanced distance protection scheme for long transmission lines in electric power systems using multiple classified anfis networks","author":"Kamel","year":"2009","journal-title":"2009 Fifth International Conference on Soft Computing, Computing with Words and Perceptions in System Analysis, Decision and Control"},{"key":"10.3233\/HIS-240016_ref22","first-page":"204","article-title":"Distance relay protection for short and long transmission line","author":"Ismail","year":"2013","journal-title":"2013 5th International Conference on Modelling, Identification and Control (ICMIC)"},{"key":"10.3233\/HIS-240016_ref23","first-page":"1","article-title":"Evaluation studies of combined wavelet and neural network applications in high voltage transmission line protection","author":"Jwad","year":"2014","journal-title":"12th IET International Conference on Developments in Power System Protection (DPSP 2014)"},{"key":"10.3233\/HIS-240016_ref24","first-page":"79","article-title":"Fault detection method using ANN for power transmission line","author":"Leh","journal-title":"2020 10th IEEE International Conference on Control System, computing and Engineering (ICCSCE)"},{"issue":"3","key":"10.3233\/HIS-240016_ref25","doi-asserted-by":"crossref","first-page":"1064","DOI":"10.3390\/en16031064","article-title":"HVDC fault detection and classification with artificial neural network based on ACO-DWT method","volume":"16","author":"Jawad","year":"2023","journal-title":"Energies"},{"issue":"5","key":"10.3233\/HIS-240016_ref26","doi-asserted-by":"crossref","first-page":"7024","DOI":"10.1109\/JSEN.2020.3041737","article-title":"DC arc-fault detection based on empirical mode decomposition of arc signatures and support vector machine","volume":"21","author":"Miao","year":"2020","journal-title":"IEEE Sensors Journal"},{"key":"10.3233\/HIS-240016_ref27","doi-asserted-by":"crossref","first-page":"479","DOI":"10.1109\/ICEES51510.2021.9383768","article-title":"Fuzzy logic based fault detection and classification scheme for series faults in six phase transmission line","author":"Althi","year":"2021","journal-title":"2021 7th International Conference on Electrical Energy Systems (ICEES)"},{"key":"10.3233\/HIS-240016_ref28","doi-asserted-by":"crossref","first-page":"107102","DOI":"10.1016\/j.ijepes.2021.107102","article-title":"A deep learning based intelligent approach in detection and classification of transmission line faults","volume":"133","author":"Fahim","year":"2021","journal-title":"International Journal of Electrical Power and Energy Systems"},{"issue":"4","key":"10.3233\/HIS-240016_ref29","doi-asserted-by":"crossref","first-page":"1163","DOI":"10.1109\/61.891497","article-title":"Positional protection of transmission systems using global positioning system","volume":"15","author":"Bo","year":"2000","journal-title":"IEEE Transactions on Power Delivery"},{"key":"10.3233\/HIS-240016_ref30","first-page":"1","article-title":"The impact of the global positioning system (gps) on protection and control","volume":"30","author":"Crossley","year":"1998","journal-title":"11th International Conference on Power System Protection, Bled, Slovenia"},{"issue":"4","key":"10.3233\/HIS-240016_ref31","doi-asserted-by":"crossref","first-page":"930","DOI":"10.1109\/TPWRD.2002.803783","article-title":"A novel adaptive pmu-based transmission-line relaydesign and emtp simulation results","volume":"17","author":"Jiang","year":"2002","journal-title":"IEEE Transactions on Power Delivery"},{"key":"10.3233\/HIS-240016_ref32","unstructured":"K.-P. Brand, Substation automation handbook utility automation consulting lohmann, Bremgarten (2003), Switzerland."},{"key":"10.3233\/HIS-240016_ref33","doi-asserted-by":"crossref","unstructured":"B. Singh, N. Sharma, A. Tiwari, K. Verma and S. Singh, Applications of phasor measurement units (pmus) in electric power system networks incorporated with facts controllers, International Journal of Engineering, Science and Technology 3(3) (2011).","DOI":"10.4314\/ijest.v3i3.68423"},{"key":"10.3233\/HIS-240016_ref34","first-page":"1","article-title":"Principal components fault location based on wams\/pmu measure system","author":"Wang","year":"2011","journal-title":"2011 IEEE Power and Energy Society General Meeting"},{"key":"10.3233\/HIS-240016_ref35","doi-asserted-by":"crossref","first-page":"14","DOI":"10.1109\/CPRE.2012.6201218","article-title":"Using synchronized phasor for fault location identification","author":"Nashawati","year":"2012","journal-title":"Proceedings of the 65th Annual Conference for Protective Relay Engineers"},{"issue":"1","key":"10.3233\/HIS-240016_ref36","first-page":"395","article-title":"A fault location technique for two-terminal multisection compound transmission lines using synchronized phasor measurements","volume":"3","author":"Chih-Wen Liu","year":"2012","journal-title":"IEEE Transactions on Smart Grid"},{"issue":"10","key":"10.3233\/HIS-240016_ref37","first-page":"655","article-title":"Method to determine the fault components of power system based on description of structure and function of relay system","volume":"104","author":"Wake","year":"1984","journal-title":"The transactions of the Institute of Electrical Engineers of Japan"},{"issue":"1","key":"10.3233\/HIS-240016_ref38","doi-asserted-by":"crossref","first-page":"363","DOI":"10.1109\/59.574960","article-title":"A logic based expert system (lbes) for fault diagnosis of power system","volume":"12","author":"Park","year":"1997","journal-title":"IEEE Transactions on power systems"},{"issue":"2","key":"10.3233\/HIS-240016_ref39","doi-asserted-by":"crossref","first-page":"439","DOI":"10.1109\/TPWRS.2002.1007915","article-title":"Fault section estimation in power systems using a novel decision support system","volume":"17","author":"Huang","year":"2002","journal-title":"IEEE Transactions on Power Systems"},{"key":"10.3233\/HIS-240016_ref40","first-page":"135","article-title":"Development of an expert system for off-and on-line faults diagnosis in electric power systems","author":"Hamzeh","year":"2004","journal-title":"Proceedings of the 2004 International Conference on Information and Communication Technologies: From Theory to Applications"},{"key":"10.3233\/HIS-240016_ref41","unstructured":"M. Batiba, A. Jain and M.B. Srinivas, A web-based expert system shell for fault diagnosis and control of power equipment, In: Proceedings of the International Conference on Condition Monitoring and Diagnosis, Beijing, China, (2008). IEEE."},{"key":"10.3233\/HIS-240016_ref42","unstructured":"F. Henao, J. Amaya, R. Jaramillo and F. Monterrosa, An expert system (es) to evaluate and characterize faults in transmission lines using case-based reasoning (cbr)."},{"key":"10.3233\/HIS-240016_ref43","doi-asserted-by":"crossref","first-page":"120070","DOI":"10.1016\/j.eswa.2023.120070","article-title":"An analysis of the security of multi-area power transmission lines using fuzzy-aco","volume":"224","author":"Pal","year":"2023","journal-title":"Expert Systems with Applications"},{"key":"10.3233\/HIS-240016_ref44","doi-asserted-by":"crossref","first-page":"338","DOI":"10.1016\/S0019-9958(65)90241-X","article-title":"Fuzzy sets","volume":"8","author":"Zadeh","year":"1965","journal-title":"Information and Control"},{"key":"10.3233\/HIS-240016_ref45","doi-asserted-by":"crossref","first-page":"269","DOI":"10.1109\/TDC.1994.328391","article-title":"A fuzzy-set approach to fault-type identification in digital relaying","author":"Ferrero","year":"1994","journal-title":"Proceedings of IEEE\/PES Transmission and Distribution Conference"},{"issue":"2","key":"10.3233\/HIS-240016_ref46","doi-asserted-by":"crossref","first-page":"609","DOI":"10.1109\/TPWRD.2004.834294","article-title":"Fuzzy-logic-based fault classification scheme for digital distance protection","volume":"20","author":"Das","year":"2005","journal-title":"IEEE Transactions on Power Delivery"},{"issue":"4","key":"10.3233\/HIS-240016_ref47","doi-asserted-by":"crossref","first-page":"1093","DOI":"10.1109\/61.714467","article-title":"Fuzzy-neuro approach to fault classification for transmission line protection","volume":"13","author":"Wang","year":"1998","journal-title":"IEEE Transactions on Power Delivery"},{"issue":"3","key":"10.3233\/HIS-240016_ref48","doi-asserted-by":"crossref","first-page":"902","DOI":"10.1109\/61.871350","article-title":"A novel fuzzy neural network based distance relaying scheme","volume":"15","author":"Dash","year":"2000","journal-title":"IEEE Transactions on Power Delivery"},{"issue":"9","key":"10.3233\/HIS-240016_ref49","doi-asserted-by":"crossref","first-page":"747","DOI":"10.1016\/S0142-0615(03)00029-2","article-title":"A novel algorithm for fault classification in transmission lines using a combined adaptive network and fuzzy inference system","volume":"25","author":"Yeo","year":"2003","journal-title":"International Journal of Electrical Power and Energy Systems"},{"issue":"2","key":"10.3233\/HIS-240016_ref50","doi-asserted-by":"crossref","first-page":"891","DOI":"10.1109\/TPWRD.2003.820413","article-title":"Higher order statistics-fuzzy integrated scheme for fault classification of a series-compensated transmission line","volume":"19","author":"Pradhan","year":"2004","journal-title":"IEEE Transactions on Power Delivery"},{"issue":"2","key":"10.3233\/HIS-240016_ref51","doi-asserted-by":"crossref","first-page":"1306","DOI":"10.1109\/TPWRD.2004.834676","article-title":"Fuzzy art neural network algorithm for classifying the power system faults","volume":"20","author":"Vasilic","year":"2005","journal-title":"IEEE Transactions on Power Delivery"},{"issue":"2","key":"10.3233\/HIS-240016_ref52","doi-asserted-by":"crossref","first-page":"928","DOI":"10.1016\/j.asoc.2012.09.010","article-title":"A systematic fuzzy rule-based approach for fault classification in transmission lines","volume":"13","author":"Samantaray","year":"2013","journal-title":"Applied Soft Computing"},{"issue":"1","key":"10.3233\/HIS-240016_ref53","doi-asserted-by":"crossref","first-page":"19","DOI":"10.1016\/0378-7796(84)90041-5","article-title":"Digital travelling-wave protection of transmission lines","volume":"7","author":"Desikachar","year":"1984","journal-title":"Electric Power Systems Research"},{"issue":"3","key":"10.3233\/HIS-240016_ref54","doi-asserted-by":"crossref","first-page":"894","DOI":"10.1109\/61.193866","article-title":"Travelling wave distance protection-problem areas and solutions","volume":"3","author":"Shehab-Eldin","year":"1988","journal-title":"IEEE Transactions on Power Delivery"},{"issue":"2","key":"10.3233\/HIS-240016_ref55","doi-asserted-by":"crossref","first-page":"680","DOI":"10.1109\/61.296245","article-title":"Maximum likelihood estimation of fault location on transmission lines using travelling waves","volume":"9","author":"Ancell","year":"1994","journal-title":"IEEE Transactions on Power Delivery"},{"key":"10.3233\/HIS-240016_ref56","doi-asserted-by":"crossref","unstructured":"Ernesto, A travelling wave distance protection using principal component analysis, International Journal of Electrical Power and Energy Systems 25(6) (2003), 471\u2013479.","DOI":"10.1016\/S0142-0615(02)00096-0"},{"issue":"2","key":"10.3233\/HIS-240016_ref57","doi-asserted-by":"crossref","first-page":"552","DOI":"10.1109\/TPWRD.2008.921144","article-title":"Fault classification and faulted-phase selection based on the initial current traveling wave","volume":"24","author":"Dong","year":"2008","journal-title":"IEEE Transactions on Power Delivery"},{"issue":"4","key":"10.3233\/HIS-240016_ref58","doi-asserted-by":"crossref","first-page":"908","DOI":"10.1109\/TPWRD.2002.803729","article-title":"New algorithm to phase selection based on wavelet transform","volume":"17","author":"Youssef","year":"2002","journal-title":"IEEE Transactions on Power Delivery"},{"issue":"4","key":"10.3233\/HIS-240016_ref59","doi-asserted-by":"crossref","first-page":"1134","DOI":"10.1109\/TPWRD.2003.817511","article-title":"Study of wavelet-based ultra high speed directional transmission line protection","volume":"18","author":"Chen","year":"2003","journal-title":"IEEE Transactions on Power Delivery"},{"issue":"7","key":"10.3233\/HIS-240016_ref60","doi-asserted-by":"crossref","first-page":"459","DOI":"10.1016\/j.ijepes.2006.02.006","article-title":"Study of protection scheme for transmission line based on wavelet transient energy","volume":"28","author":"Fan","year":"2006","journal-title":"International Journal of Electrical Power and Energy Systems"},{"issue":"1","key":"10.3233\/HIS-240016_ref61","doi-asserted-by":"crossref","first-page":"47","DOI":"10.1080\/15325000691001485","article-title":"Comparison of fault classification methods based on wavelet analysis and ann","volume":"34","author":"Mahanty","year":"2006","journal-title":"Electric Power Components and Systems"},{"key":"10.3233\/HIS-240016_ref62","first-page":"1","article-title":"Combined wavelet transform and neural network (wnn) based fault detection and classification in transmission lines","author":"Geethanjali","year":"2009","journal-title":"2009 International Conference on Control, Automation, Communication and Energy Conservation"},{"key":"10.3233\/HIS-240016_ref63","first-page":"1","article-title":"Discrete wavelet transform and back-propagation neural networks algorithm for fault classification on transmission line","author":"Pothisarn","year":"2009","journal-title":"2009 Transmission and Distribution Conference and Exposition: Asia and Pacific"},{"key":"10.3233\/HIS-240016_ref64","doi-asserted-by":"crossref","first-page":"579","DOI":"10.1109\/PEOCO.2010.5559232","article-title":"Comparison of fourier and wavelet transform methods for transmission line fault classification","author":"Abdollahi","year":"2010","journal-title":"2010 4th International Power Engineering and Optimization Conference (PEOCO)"},{"key":"10.3233\/HIS-240016_ref65","doi-asserted-by":"crossref","unstructured":"A. Ngaopitakkul and S. Bunjongjit, An application of a discrete wavelet transform and a backpropagation neural network algorithm for fault diagnosis on single-circuit transmission line, International Journal of Systems Science 44(9).","DOI":"10.1080\/00207721.2012.670290"},{"key":"10.3233\/HIS-240016_ref66","unstructured":"V. Vapnik, Statistical learning theory, J Wiley (1998), New York."},{"key":"10.3233\/HIS-240016_ref67","unstructured":"B. Sch\u00f6lkopf, C.J. Burges and A.J. Smola, Advances in Kernel Methods: Support Vector Learning, MIT Press (1999)."},{"key":"10.3233\/HIS-240016_ref68","first-page":"196","article-title":"Face recognition by support vector machines","author":"Guo","year":"2000","journal-title":"Proceedings Fourth IEEE International Conference on Automatic Face and Gesture Recognition"},{"key":"10.3233\/HIS-240016_ref69","doi-asserted-by":"crossref","first-page":"5614","DOI":"10.1109\/SICE.2006.315099","article-title":"Nonlinear system identification based on support vector machine using particle swarm optimization","author":"Lee","year":"2006","journal-title":"2006 SICE-ICASE International Joint Conference"},{"key":"10.3233\/HIS-240016_ref70","first-page":"2","article-title":"Time series prediction based on svm and ga","author":"Weiwei","year":"2007","journal-title":"2007 8th International Conference on Electronic Measurement and Instruments"},{"key":"10.3233\/HIS-240016_ref71","first-page":"1152","article-title":"Svm in oracle database 10g: removing the barriers to widespread adoption of support vector machines","author":"Milenova","year":"2005","journal-title":"Proceedings of the 31st International Conference on Very Large Data Bases"},{"key":"10.3233\/HIS-240016_ref72","unstructured":"M. Welling, Support Vector Machines, University of Toronto (2004), Toronto, Canada."},{"issue":"1","key":"10.3233\/HIS-240016_ref73","doi-asserted-by":"crossref","first-page":"67","DOI":"10.1109\/TPWRD.2006.876695","article-title":"Fault classification and section identification of an advanced series-compensated transmission line using support vector machine","volume":"22","author":"Dash","year":"2006","journal-title":"IEEE Transactions on Power Delivery"},{"issue":"1","key":"10.3233\/HIS-240016_ref74","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.epsr.2004.07.008","article-title":"Fault diagnosis of power transformer based on multi-layer svm classifier","volume":"74","author":"Ganyun","year":"2005","journal-title":"Electric Power Systems Research"},{"key":"10.3233\/HIS-240016_ref75","unstructured":"T. Dhadbanjan and H. Khincha, Intelligent approach for fault diagnosis in power transmission systems using support vector machines, International Journal of Emerging Electric Power Systems 8(4)."},{"key":"10.3233\/HIS-240016_ref76","doi-asserted-by":"crossref","first-page":"1256","DOI":"10.1109\/WCICA.2008.4593104","article-title":"Application of svm in fault diagnosis of power electronics rectifier","author":"Wang","year":"2008","journal-title":"2008 7th World Congress on Intelligent Control and Automation"},{"issue":"12","key":"10.3233\/HIS-240016_ref77","doi-asserted-by":"crossref","first-page":"8822","DOI":"10.1016\/j.eswa.2010.06.016","article-title":"Accurate fault location on ehv lines using both rbf based support vector machine and scalcg based neural network","volume":"37","author":"Gayathri","year":"2010","journal-title":"Expert Systems with Applications"},{"issue":"1","key":"10.3233\/HIS-240016_ref78","doi-asserted-by":"crossref","first-page":"188","DOI":"10.1109\/TPWRD.2012.2215925","article-title":"High-frequency transients-based protection of multiterminal transmission lines using the svm technique","volume":"28","author":"Jafarian","year":"2012","journal-title":"IEEE Transactions on Power Delivery"},{"key":"10.3233\/HIS-240016_ref79","doi-asserted-by":"publisher","DOI":"10.1186\/s41601-016-0029-6"},{"key":"10.3233\/HIS-240016_ref80","first-page":"447","article-title":"Adaptive relaying using artificial neural network","author":"Khaparde","year":"1992","journal-title":"Proceedings of the Second International Forum on Applications of Neural Networks to Power Systems"},{"key":"10.3233\/HIS-240016_ref81","doi-asserted-by":"crossref","first-page":"226","DOI":"10.1109\/ISAP.1996.501073","article-title":"An artificial neural network application to distance protection [of power systems]","author":"Qi","year":"1996","journal-title":"Proceedings of International Conference on Intelligent System Application to Power Systems"},{"issue":"1","key":"10.3233\/HIS-240016_ref82","doi-asserted-by":"crossref","first-page":"102","DOI":"10.1109\/61.660861","article-title":"Artificial neural network approach to distance protection of transmission lines","volume":"13","author":"Coury","year":"1998","journal-title":"IEEE Transactions on Power Delivery"},{"issue":"2","key":"10.3233\/HIS-240016_ref83","doi-asserted-by":"crossref","first-page":"349","DOI":"10.1109\/61.754073","article-title":"An ann based approach to improve the speed of a differential equation based distance relaying algorithm","volume":"14","author":"Cho","year":"1999","journal-title":"IEEE Transactions on Power Delivery"},{"issue":"3","key":"10.3233\/HIS-240016_ref84","doi-asserted-by":"crossref","first-page":"173","DOI":"10.1016\/S0378-7796(99)00058-9","article-title":"High-speed transmission relaying using artificial neural networks","volume":"53","author":"Zahra","year":"2000","journal-title":"Electric Power Systems Research"},{"issue":"1","key":"10.3233\/HIS-240016_ref85","doi-asserted-by":"crossref","first-page":"370","DOI":"10.1109\/59.852146","article-title":"Artificial neural network approach to single-ended fault locator for transmission lines","volume":"15","author":"Chen","year":"2000","journal-title":"IEEE Transactions on Power Systems"},{"issue":"6","key":"10.3233\/HIS-240016_ref86","doi-asserted-by":"crossref","first-page":"491","DOI":"10.1016\/S0142-0615(00)00068-5","article-title":"Ann applications in fault locators","volume":"23","author":"Purushothama","year":"2001","journal-title":"International Journal of Electrical Power and Energy Systems"},{"issue":"2","key":"10.3233\/HIS-240016_ref87","doi-asserted-by":"crossref","first-page":"219","DOI":"10.1109\/61.915486","article-title":"Ann-based techniques for estimating fault location on transmission lines using prony method","volume":"16","author":"Tawfik","year":"2001","journal-title":"IEEE Transactions on Power Delivery"},{"issue":"1","key":"10.3233\/HIS-240016_ref88","doi-asserted-by":"crossref","first-page":"341","DOI":"10.1016\/j.asoc.2008.04.011","article-title":"A transmission line fault locator based on Elman recurrent networks","volume":"9","author":"Ekici","year":"2009","journal-title":"Applied Soft Computing"},{"issue":"1","key":"10.3233\/HIS-240016_ref89","doi-asserted-by":"crossref","first-page":"75","DOI":"10.1109\/61.905596","article-title":"A real-time hardware fault detector using an artificial neural network for distance protection","volume":"16","author":"Venkatesan","year":"2001","journal-title":"IEEE Transactions on Power Delivery"},{"issue":"1","key":"10.3233\/HIS-240016_ref90","doi-asserted-by":"crossref","first-page":"68","DOI":"10.1109\/61.905593","article-title":"Application of minimal radial basis function neural network to distance protection","volume":"16","author":"Dash","year":"2001","journal-title":"IEEE Transactions on Power Delivery"},{"issue":"1","key":"10.3233\/HIS-240016_ref91","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/S0378-7796(01)00150-X","article-title":"A fast and accurate distance relaying scheme using an efficient radial basis function neural network","volume":"60","author":"Pradhan","year":"2001","journal-title":"Electric Power Systems Research"},{"key":"10.3233\/HIS-240016_ref92","doi-asserted-by":"crossref","unstructured":"Y.-H. Song, A. Johns, Q. Xuan and J. Liu, Genetic algorithm based neural networks applied to fault classification for EHV transmission lines with a UPFC, (1997).","DOI":"10.1049\/cp:19970081"},{"issue":"4","key":"10.3233\/HIS-240016_ref93","doi-asserted-by":"crossref","first-page":"1093","DOI":"10.1109\/61.714467","article-title":"Fuzzy-neuro approach to fault classification for transmission line protection","volume":"13","author":"Wang","year":"1998","journal-title":"IEEE Transactions on Power Delivery"},{"key":"10.3233\/HIS-240016_ref94","first-page":"1","article-title":"Faulted phase selection on double circuit transmission line using wavelet transform and neural network","author":"Kale","year":"2009","journal-title":"2009 International Conference on Power Systems"},{"key":"10.3233\/HIS-240016_ref95","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1155\/2013\/271865","article-title":"Artificial neural network-based fault distance locator for double-circuit transmission lines","author":"Jain","year":"2013","journal-title":"Advances in Artificial Intelligence"},{"issue":"3","key":"10.3233\/HIS-240016_ref96","doi-asserted-by":"crossref","first-page":"373","DOI":"10.1049\/iet-gtd.2013.0239","article-title":"Improved first zone reach setting of ANN based directional relay for protection of double circuit transmission lines","volume":"8","author":"Yadav","year":"2014","journal-title":"IET Generation, Transmission and Distribution"},{"key":"10.3233\/HIS-240016_ref97","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1109\/SPIN.2014.6776911","article-title":"Fault classification of phase to phase fault in six phase transmission line using Haar wavelet and ANN","author":"Kumar","year":"2014","journal-title":"2014 International Conference on Signal Processing and Integrated Networks (SPIN)"},{"issue":"5","key":"10.3233\/HIS-240016_ref98","doi-asserted-by":"crossref","first-page":"2270","DOI":"10.1109\/TII.2017.2682101","article-title":"Optimal Protection Coordination for Microgrids Considering N -1 Contingency","volume":"13","author":"Saleh","year":"2017","journal-title":"IEEE Transactions on Industrial Informatics"},{"key":"10.3233\/HIS-240016_ref99","doi-asserted-by":"crossref","first-page":"102235","DOI":"10.1109\/ACCESS.2020.2996969","article-title":"Modeling and fault categorization in thin-film and crystalline PV arrays through multilayer neural network algorithm","volume":"8","author":"Ul-Haq","year":"2020","journal-title":"IEEE Access"},{"key":"10.3233\/HIS-240016_ref100","first-page":"1","article-title":"Probabilistic neural network-aided fast classification of transmission line faults using differencing of current signal","author":"Mukherjee","year":"2021","journal-title":"Journal of The Institution of Engineers (India): Series B"},{"key":"10.3233\/HIS-240016_ref101","doi-asserted-by":"crossref","first-page":"106360","DOI":"10.1016\/j.epsr.2020.106360","article-title":"Probabilistic transmission line fault diagnosis using autonomous neural models","volume":"185","author":"Ferreira","year":"2020","journal-title":"Electric Power Systems Research"},{"key":"10.3233\/HIS-240016_ref102","first-page":"1179","article-title":"Study on health monitoring system of deep foundation pit operator of the transmission line based on residual network","volume":"12979","author":"Qian","journal-title":"Ninth International Conference on Energy Materials and Electrical Engineering (ICEMEE 2023)"},{"issue":"1","key":"10.3233\/HIS-240016_ref103","doi-asserted-by":"crossref","first-page":"2450008","DOI":"10.1142\/S0219467824500086","article-title":"Optimization-Assisted CNN Model for Fault Classification and Site Location in Transmission Lines","volume":"24","author":"Kumar","year":"2024","journal-title":"International Journal of Image and Graphics"},{"key":"10.3233\/HIS-240016_ref104","doi-asserted-by":"crossref","unstructured":"A. Moradzadeh, H. Teimourzadeh, B. Mohammadi-Ivatloo and K. Pourhossein, Hybrid CNN-LSTM approaches for identification of type and locations of trans, (2022).","DOI":"10.1016\/j.ijepes.2021.107563"},{"key":"10.3233\/HIS-240016_ref105","doi-asserted-by":"crossref","first-page":"781","DOI":"10.1016\/j.egyr.2022.02.275","article-title":"Fault location of transmission line based on CNN-LSTM double-ended combined model","volume":"8","author":"Wang","year":"2022","journal-title":"Energy Reports"},{"key":"10.3233\/HIS-240016_ref106","first-page":"57","article-title":"Fault Classification in an IEEE 30 Bus System using Convolutional Neural Network","author":"Tikariha","year":"2021","journal-title":"4th International Conference on Recent Developments in Control, Automation and Power Engineering (RDCAPE)"},{"key":"10.3233\/HIS-240016_ref107","doi-asserted-by":"crossref","unstructured":"M. Gilanifar, H. Wang, J. Cordova, E.E. Ozguven, T.I. Strasser and R. Arghandeh, Fault classification in power distribution systems based on limited labeled data using multi-task latent structure learning, Sustainable Cities and Society 73 (2021).","DOI":"10.1016\/j.scs.2021.103094"},{"key":"10.3233\/HIS-240016_ref108","doi-asserted-by":"crossref","unstructured":"P. Srikanth and C. Koley, A novel three-dimensional deep learning algorithm for classification of power system faults, Computers and Electrical Engineering 91 (2021).","DOI":"10.1016\/j.compeleceng.2021.107100"},{"key":"10.3233\/HIS-240016_ref109","doi-asserted-by":"crossref","unstructured":"S.R. Fahim, S.K. Sarker, S.M. Muyeen, S.K. Das and I. Kamwa, A deep learning based intelligent approach in detection and classification of transmission line faults, International Journal of Electrical Power and Energy Systems 133 (2021).","DOI":"10.1016\/j.ijepes.2021.107102"},{"key":"10.3233\/HIS-240016_ref110","doi-asserted-by":"crossref","unstructured":"F. Rafique, L. Fu and R. Mai, End to end machine learning for fault detection and classification in power transmission lines, Electric Power Systems Research 199 (2021).","DOI":"10.1016\/j.epsr.2021.107430"},{"key":"10.3233\/HIS-240016_ref111","doi-asserted-by":"crossref","unstructured":"Z. Mustafa, A.S.A. Awad, M. Azzouz and A. Azab, Fault identification for photovoltaic systems using a multi-output deep learning approach, Expert Systems with Applications 211 (2022).","DOI":"10.2139\/ssrn.4067065"},{"issue":"1","key":"10.3233\/HIS-240016_ref112","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1109\/TIM.2023.3238059","article-title":"CNN-Based Transformer Model for Fault Detection in Power System Networks","volume":"72","author":"Thomas","year":"2023","journal-title":"IEEE Transactions on Instrumentation and Measurement"},{"issue":"2","key":"10.3233\/HIS-240016_ref113","doi-asserted-by":"crossref","first-page":"e0295144","DOI":"10.1371\/journal.pone.0295144","article-title":"Ensemble learning based transmission line fault classification using phasor measurement unit (PMU) data with explainable AI (XAI)","volume":"19","author":"Bin Akter","year":"2024","journal-title":"Plos One"},{"key":"10.3233\/HIS-240016_ref114","doi-asserted-by":"crossref","first-page":"110105","DOI":"10.1016\/j.epsr.2023.110105","article-title":"A fault recognition method for transmission systems based on independent component analysis and convolutional neural networks","volume":"229","author":"de Alencar","year":"2024","journal-title":"Electric Power Systems Research"}],"container-title":["International Journal of Hybrid Intelligent Systems"],"original-title":[],"link":[{"URL":"https:\/\/content.iospress.com\/download?id=10.3233\/HIS-240016","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,29]],"date-time":"2026-04-29T08:53:04Z","timestamp":1777452784000},"score":1,"resource":{"primary":{"URL":"https:\/\/journals.sagepub.com\/doi\/full\/10.3233\/HIS-240016"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,9,19]]},"references-count":114,"journal-issue":{"issue":"3"},"URL":"https:\/\/doi.org\/10.3233\/his-240016","relation":{},"ISSN":["1448-5869","1875-8819"],"issn-type":[{"value":"1448-5869","type":"print"},{"value":"1875-8819","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,9,19]]}}}