{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,24]],"date-time":"2026-03-24T20:02:59Z","timestamp":1774382579930,"version":"3.50.1"},"reference-count":33,"publisher":"Springer Science and Business Media LLC","issue":"3","license":[{"start":{"date-parts":[[2021,11,10]],"date-time":"2021-11-10T00:00:00Z","timestamp":1636502400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2021,11,10]],"date-time":"2021-11-10T00:00:00Z","timestamp":1636502400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Int J Syst Assur Eng Manag"],"published-print":{"date-parts":[[2022,6]]},"DOI":"10.1007\/s13198-021-01487-z","type":"journal-article","created":{"date-parts":[[2021,11,10]],"date-time":"2021-11-10T04:38:24Z","timestamp":1636519104000},"page":"1419-1429","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Demand side maximum loading limit ranking based on composite index using ANN"],"prefix":"10.1007","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7958-2132","authenticated-orcid":false,"given":"Alok Nath","family":"Yadav","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kirti","family":"Pal","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2021,11,10]]},"reference":[{"key":"1487_CR1","doi-asserted-by":"publisher","unstructured":"Abiodun OI et al (2018) State-of-the-art in artificial neural network Applications: A survey. 4(11), Heliyon e00938, Doi: https:\/\/doi.org\/10.1016\/j.heliyon.2018.e00938","DOI":"10.1016\/j.heliyon.2018.e00938"},{"key":"1487_CR2","doi-asserted-by":"publisher","unstructured":"Advani MS et al (2020) High-dimensional dynamics of generalization error in neural networks. Neural Networks 132 ) 428\u2013446. Doi: https:\/\/doi.org\/10.1016\/j.neunet.2020.08.022","DOI":"10.1016\/j.neunet.2020.08.022"},{"issue":"1","key":"1487_CR3","doi-asserted-by":"publisher","first-page":"416","DOI":"10.1109\/59.141737","volume":"7","author":"V Ajjarapu","year":"1992","unstructured":"Ajjarapu V, Christy C (1992) The continuation power flow: a tool for steady state voltage stability analysis. IEEE Trans Power Syst 7(1):416\u2013423. https:\/\/doi.org\/10.1109\/59.141737","journal-title":"IEEE Trans Power Syst"},{"issue":"4","key":"1487_CR4","doi-asserted-by":"publisher","first-page":"682","DOI":"10.3390\/en12040682","volume":"12","author":"H Alhelou","year":"2019","unstructured":"Alhelou H et al (2019) A Survey on power system blackout and cascading events: research motivations and challenges. Energies 12(4):682. https:\/\/doi.org\/10.3390\/en12040682","journal-title":"Energies"},{"key":"1487_CR5","doi-asserted-by":"publisher","unstructured":"Althowibi FA, Mustafa MW (2010) Voltage stability calculations in power transmission lines: Indications and allocations. IEEE International Conference on Power and Energy 390\u2013395, Kuala Lumpur, Malaysia. doi: https:\/\/doi.org\/10.1109\/PECON.2010.5697615","DOI":"10.1109\/PECON.2010.5697615"},{"key":"1487_CR6","doi-asserted-by":"publisher","first-page":"122","DOI":"10.1016\/j.egypro.2017.11.055","volume":"49","author":"SD Anagnostatos","year":"2013","unstructured":"Anagnostatos SD et al (2013) Examination of the 2006 blackout in Kefallonia island, Greece. Int J Electr Power Energy Syst 49:122\u2013127. https:\/\/doi.org\/10.1016\/j.egypro.2017.11.055","journal-title":"Int J Electr Power Energy Syst"},{"issue":"32","key":"1487_CR7","doi-asserted-by":"publisher","first-page":"15849","DOI":"10.1073\/pnas.1903070116","volume":"116","author":"M Belkin","year":"2019","unstructured":"Belkin M et al (2019) Reconciling modern machine learning practice and the classical bias\u2013variance trade-off. Proc Natl Acad Sci 116(32):15849\u201315854. https:\/\/doi.org\/10.1073\/pnas.1903070116","journal-title":"Proc Natl Acad Sci"},{"issue":"4","key":"1487_CR8","doi-asserted-by":"publisher","first-page":"1167","DOI":"10.1137\/20M1336072","volume":"2","author":"M Belkin","year":"2020","unstructured":"Belkin M et al (2020) Two models of double descent for weak features. SIAM J Math Data Sci 2(4):1167\u20131180. https:\/\/doi.org\/10.1137\/20M1336072","journal-title":"SIAM J Math Data Sci"},{"issue":"2","key":"1487_CR9","doi-asserted-by":"publisher","first-page":"673","DOI":"10.1109\/59.141773","volume":"7","author":"CA Canizares","year":"1992","unstructured":"Canizares CA et al (1992) Point of collapse methods applied to AC\/DC power systems. IEEE Trans Power Syst 7(2):673\u2013683. https:\/\/doi.org\/10.1109\/59.141773","journal-title":"IEEE Trans Power Syst"},{"issue":"1\u20133","key":"1487_CR10","doi-asserted-by":"publisher","first-page":"506","DOI":"10.1016\/j.neucom.2009.06.012","volume":"73","author":"KT Chaturvedi","year":"2009","unstructured":"Chaturvedi KT et al (2009) Hybrid fuzzy-neural network-based composite contingency ranking employing fuzzy curvesfor featureselection. Neurocomputing 73(1\u20133):506\u2013516. https:\/\/doi.org\/10.1016\/j.neucom.2009.06.012","journal-title":"Neurocomputing"},{"key":"1487_CR11","doi-asserted-by":"publisher","unstructured":"Cutsem TV, Vournas C (1998) Voltage stability of electrical power systems.New York, Springer Science, NewYork, USA. https:\/\/doi.org\/10.1007\/978-0-387-75536-6","DOI":"10.1007\/978-0-387-75536-6"},{"key":"1487_CR12","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1155\/2020\/8037837","volume":"2020","author":"LV Dai","year":"2020","unstructured":"Dai LV et al (2020) An innovatory method based on continuation power flow to analyze power system voltage stability with distributed generation penetration. Complexity 2020:1\u201315. https:\/\/doi.org\/10.1155\/2020\/8037837","journal-title":"Complexity"},{"key":"1487_CR13","doi-asserted-by":"publisher","first-page":"307","DOI":"10.1007\/BF02429868","volume":"3","author":"I Dobson","year":"1993","unstructured":"Dobson I (1993) Computing a closest bifurcation instability in multidimensional parameter space. J Nonlinear Sci 3:307\u2013327. https:\/\/doi.org\/10.1007\/BF02429868","journal-title":"J Nonlinear Sci"},{"issue":"1","key":"1487_CR14","doi-asserted-by":"publisher","first-page":"223","DOI":"10.1109\/59.852125","volume":"15","author":"AJ Flueck","year":"2000","unstructured":"Flueck AJ, Dondeti JR (2000) A new continuation power flow tool for investigating the nonlinear effects of transmission branch parameter variations. IEEE Trans Power Syst 15(1):223\u2013227. https:\/\/doi.org\/10.1109\/59.852125","journal-title":"IEEE Trans Power Syst"},{"key":"1487_CR15","doi-asserted-by":"publisher","unstructured":"Gupta A et al (2019) Artificial neural networks: Its techniques and applications to forecasting. International Conference on Automation, Computational and Technology Management (ICACTM). 320\u2013324. doi: https:\/\/doi.org\/10.1109\/ICACTM.2019.8776701","DOI":"10.1109\/ICACTM.2019.8776701"},{"key":"1487_CR16","doi-asserted-by":"publisher","unstructured":"Huang GM et al (2002) A new bifurcation analysis for power system dynamic voltage stability studies. IEEE Power Engineering Society Winter Meeting. Conference Proceedings (Cat. No.02CH37309), New York, pp. 882\u2013887, NY, USA . doi: https:\/\/doi.org\/10.1109\/PESW.2002.985133","DOI":"10.1109\/PESW.2002.985133"},{"issue":"2","key":"1487_CR17","doi-asserted-by":"publisher","first-page":"584","DOI":"10.1109\/59.76701","volume":"6","author":"Suzuki K Iba","year":"1991","unstructured":"Iba Suzuki K, Egawa HM, Watanabe T (1991) Calculation of critical loading condition with nose curve using homotopy continuation method. IEEE Trans Power Syst 6(2):584\u2013593. https:\/\/doi.org\/10.1109\/59.76701","journal-title":"IEEE Trans Power Syst"},{"key":"1487_CR18","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.rser.2016.05.010","volume":"63","author":"M Javad","year":"2016","unstructured":"Javad M et al (2016) A comprehensive review of the voltage stability indices. Renew Sustain Energy Rev 63:1\u201312. https:\/\/doi.org\/10.1016\/j.rser.2016.05.010","journal-title":"Renew Sustain Energy Rev"},{"issue":"16\u201318","key":"1487_CR19","doi-asserted-by":"publisher","first-page":"3005","DOI":"10.1016\/j.neucom.2010.07.006","volume":"73","author":"V Jayasankar","year":"2010","unstructured":"Jayasankar V et al (2010) Estimation of voltage stability index for power system employing artificial neural network technique and TCSC placement. Neurocomputing 73(16\u201318):3005\u20133011. https:\/\/doi.org\/10.1016\/j.neucom.2010.07.006","journal-title":"Neurocomputing"},{"issue":"3","key":"1487_CR20","doi-asserted-by":"publisher","first-page":"1387","DOI":"10.1109\/TPWRS.2004.825981","volume":"19","author":"P Kundur","year":"2004","unstructured":"Kundur P et al (2004) Definition and classification of power system stability IEEE\/CIGRE joint task force on stability terms and definitions. IEEE Trans Power Syst 19(3):1387\u20131401. https:\/\/doi.org\/10.1109\/TPWRS.2004.825981","journal-title":"IEEE Trans Power Syst"},{"key":"1487_CR21","doi-asserted-by":"publisher","unstructured":"Magalhaes E de M, Neto AB, Alves DA (2012) A parameterization technique for the continuation power flow developed from the analysis of power flow curves\u201d, Mathematical Problems in Engineering 2012, Article ID 762371, 1\u201324. doi:https:\/\/doi.org\/10.1155\/2012\/762371.","DOI":"10.1155\/2012\/762371"},{"issue":"1","key":"1487_CR22","doi-asserted-by":"publisher","first-page":"55","DOI":"10.12720\/ijoee.1.1.55-60","volume":"1","author":"H Marefatjou","year":"2013","unstructured":"Marefatjou H, Soltani I (2013) Continuation power flow method with improved voltage stability analysis in two area power system. Int J Electr Energy 1(1):55\u201360. https:\/\/doi.org\/10.12720\/ijoee.1.1.55-60","journal-title":"Int J Electr Energy"},{"issue":"11","key":"1487_CR23","doi-asserted-by":"publisher","first-page":"50","DOI":"10.1109\/MPER.2002.4311799","volume":"22","author":"I Musirin","year":"2002","unstructured":"Musirin I, Rahman TKA (2002) Estimating maximum loadability for weak bus identification using FVSI. IEEE Power Eng Rev 22(11):50\u201352. https:\/\/doi.org\/10.1109\/MPER.2002.4311799","journal-title":"IEEE Power Eng Rev"},{"key":"1487_CR24","doi-asserted-by":"publisher","unstructured":"Pal K et al (2013) Market power assessment using hybrid fuzzy neural network. In: Jordanov I., Jain L.C. (eds) Innovations in Intelligent Machines -3. Studies in Computational Intelligence, 442, Springer, Berlin, Heidelberg 15\u201335. Doi: https:\/\/doi.org\/10.1007\/978-3-642-32177-1_2","DOI":"10.1007\/978-3-642-32177-1_2"},{"key":"1487_CR25","doi-asserted-by":"publisher","unstructured":"Pal K et al (2016) Levenberg-Marquardt algorithm based ANN for nodal price prediction in restructured power system. In: Karampelas P., Ekonomou L. (eds) Electricity Distribution. Energy Systems. Springer, Berlin, Heidelberg. 297\u2013318. Doi: https:\/\/doi.org\/10.1007\/978-3-662-49434-9_13","DOI":"10.1007\/978-3-662-49434-9_13"},{"issue":"3","key":"1487_CR26","doi-asserted-by":"publisher","first-page":"1822","DOI":"10.1109\/TPWRS.2019.2944747","volume":"35","author":"J Pono\u0107ko","year":"2020","unstructured":"Pono\u0107ko J, Milanovi\u0107 JV (2020) Multi-objective demand side management at distribution network level in support of transmission network operation. IEEE Trans Power Syst 35(3):1822\u20131833. https:\/\/doi.org\/10.1109\/TPWRS.2019.2944747","journal-title":"IEEE Trans Power Syst"},{"key":"1487_CR27","doi-asserted-by":"publisher","unstructured":"Sarkar S et al (2015) Indian experience on smart grid application in blackout control. In Proceedings of the 2015 National Systems Conference (NSC), Noida, India,(2015). DOI:\u00a0https:\/\/doi.org\/10.1109\/NATSYS.2015.7489079","DOI":"10.1109\/NATSYS.2015.7489079"},{"key":"1487_CR28","doi-asserted-by":"publisher","unstructured":"Schadwick JE (2013) How a smarter grid could have prevented the 2003 U.S. cascading blackout. IEEE Power and Energy Conference at Illinois (PECI), Urbana, IL, USA 65\u201371. Doi: https:\/\/doi.org\/10.1109\/PECI.2013.6506036","DOI":"10.1109\/PECI.2013.6506036"},{"key":"1487_CR29","unstructured":"Seydel R (2010) From equilibrium to chaos: practical bifurcation and stability analysis 5, 2nd edition, Springer, New York, NY, USA ISBN 978-1-4419-1739-3"},{"key":"1487_CR30","doi-asserted-by":"publisher","DOI":"10.1109\/TPAS.1983.318052","author":"Y Tamura","year":"1983","unstructured":"Tamura Y et al (1983) Relationship between voltage instability and multiple load flow solutions in electric power systems. IEEE Trans Power Appar Syst. https:\/\/doi.org\/10.1109\/TPAS.1983.318052","journal-title":"IEEE Trans Power Appar Syst"},{"key":"1487_CR31","doi-asserted-by":"publisher","unstructured":"Vahdati PM et al (2018) Hopf Bifurcation control of power system nonlinear dynamics via a dynamic state feedback controller\u2013Part I: Theory and Modeling. IEEE Power & Energy Society General Meeting (PESGM), Portland, OR 1\u20131, USA doi: https:\/\/doi.org\/10.1109\/PESGM.2018.8586656","DOI":"10.1109\/PESGM.2018.8586656"},{"issue":"4","key":"1487_CR32","doi-asserted-by":"publisher","first-page":"857","DOI":"10.3390\/en13040857","volume":"13","author":"WM Villa-Acevedo","year":"2020","unstructured":"Villa-Acevedo WM et al (2020) Voltage stability margin index estimation using a hybrid kernel extreme learning machine approach. Energies 13(4):857. https:\/\/doi.org\/10.3390\/en13040857","journal-title":"Energies"},{"key":"1487_CR33","doi-asserted-by":"publisher","unstructured":"Wan H (2017) Load forecasting via Deep Neural Networks. Elsevier Procedia Computer Science 122 308\u2013314. Doi: https:\/\/doi.org\/10.1016\/j.procs.2017.11.374","DOI":"10.1016\/j.procs.2017.11.374"}],"container-title":["International Journal of System Assurance Engineering and Management"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s13198-021-01487-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s13198-021-01487-z\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s13198-021-01487-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,5,26]],"date-time":"2022-05-26T10:40:16Z","timestamp":1653561616000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s13198-021-01487-z"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,11,10]]},"references-count":33,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2022,6]]}},"alternative-id":["1487"],"URL":"https:\/\/doi.org\/10.1007\/s13198-021-01487-z","relation":{},"ISSN":["0975-6809","0976-4348"],"issn-type":[{"value":"0975-6809","type":"print"},{"value":"0976-4348","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,11,10]]},"assertion":[{"value":"1 July 2021","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"15 September 2021","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"27 October 2021","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"10 November 2021","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"Alok Nath Yadav and Kirti Pal declare that they have no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}