{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,3]],"date-time":"2026-04-03T06:57:06Z","timestamp":1775199426167,"version":"3.50.1"},"reference-count":28,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2021,10,26]],"date-time":"2021-10-26T00:00:00Z","timestamp":1635206400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2021,10,26]],"date-time":"2021-10-26T00:00:00Z","timestamp":1635206400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"funder":[{"DOI":"10.13039\/501100015832","name":"effat university","doi-asserted-by":"crossref","award":["UC#9\/29 April.2020\/7.1-22(2)3"],"award-info":[{"award-number":["UC#9\/29 April.2020\/7.1-22(2)3"]}],"id":[{"id":"10.13039\/501100015832","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["SN COMPUT. SCI."],"published-print":{"date-parts":[[2022,1]]},"DOI":"10.1007\/s42979-021-00904-1","type":"journal-article","created":{"date-parts":[[2021,10,26]],"date-time":"2021-10-26T13:05:40Z","timestamp":1635253540000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":17,"title":["Machine Learning with Adaptive Rate Processing for Power Quality Disturbances Identification"],"prefix":"10.1007","volume":"3","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4268-3482","authenticated-orcid":false,"given":"Saeed","family":"Mian Qaisar","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Nehal","family":"Alyamani","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Asad","family":"Waqar","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Moez","family":"Krichen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2021,10,26]]},"reference":[{"key":"904_CR1","doi-asserted-by":"publisher","first-page":"281","DOI":"10.1016\/j.apenergy.2018.07.058","volume":"229","author":"G Van den Broeck","year":"2018","unstructured":"Van den Broeck G, Stuyts J, Driesen J. A critical review of power quality standards and definitions applied to DC microgrids. Appl Energy. 2018;229:281\u20138.","journal-title":"Appl Energy"},{"key":"904_CR2","doi-asserted-by":"publisher","first-page":"71","DOI":"10.1109\/ICETEESES.2016.7581355","volume":"2016","author":"V Kumar","year":"2016","unstructured":"Kumar V, Pandey AS, Sinha SK. Grid integration and power quality issues of wind and solar energy system: a review. Int Conf Emerg Trends Electr Electron Sustain Energy Syst (ICETEESES). 2016;2016:71\u201380.","journal-title":"Int Conf Emerg Trends Electr Electron Sustain Energy Syst (ICETEESES)"},{"issue":"10","key":"904_CR3","doi-asserted-by":"crossref","first-page":"49","DOI":"10.1016\/j.tej.2016.11.006","volume":"29","author":"S R\u00f6nnberg","year":"2016","unstructured":"R\u00f6nnberg S, Bollen M. Power quality issues in the electric power system of the future. Electr J. 2016;29(10):49\u201361.","journal-title":"Electr J"},{"issue":"2","key":"904_CR4","first-page":"7","volume":"1","author":"ND Ali","year":"2018","unstructured":"Ali ND, Zakri AA. Identifying characteristic of power quality problems on solar electric power generation. Int J Electr Energy Power Syst Eng. 2018;1(2):7\u201310.","journal-title":"Int J Electr Energy Power Syst Eng"},{"issue":"7","key":"904_CR5","doi-asserted-by":"publisher","first-page":"1312","DOI":"10.1049\/iet-pel.2014.0531","volume":"8","author":"MB Latran","year":"2015","unstructured":"Latran MB, Teke A, Yolda\u015f Y. Mitigation of power quality problems using distribution static synchronous compensator: a comprehensive review. IET Power Electron. 2015;8(7):1312\u201328.","journal-title":"IET Power Electron"},{"key":"904_CR6","doi-asserted-by":"publisher","first-page":"528","DOI":"10.1109\/PES.2004.1372855","volume":"1","author":"A Thapar","year":"2004","unstructured":"Thapar A, Saha TK, Dong ZY. Investigation of power quality categorisation and simulating it\u2019s impact on sensitive electronic equipment. IEEE Power Eng Soc General Meet. 2004;1:528\u201333. https:\/\/doi.org\/10.1109\/PES.2004.1372855.","journal-title":"IEEE Power Eng Soc General Meet"},{"key":"904_CR7","doi-asserted-by":"crossref","unstructured":"R. A. Flores, \u201cState of the art in the classification of power quality events, an overview,\u201d in 10th International Conference on Harmonics and Quality of Power. Proceedings (Cat. No. 02EX630), 2002, vol. 1, pp. 17\u201320.","DOI":"10.1109\/ICHQP.2002.1221398"},{"key":"904_CR8","doi-asserted-by":"publisher","first-page":"334","DOI":"10.1016\/j.rser.2015.11.064","volume":"56","author":"KW Kow","year":"2016","unstructured":"Kow KW, Wong YW, Rajkumar RK, Rajkumar RK. A review on performance of artificial intelligence and conventional method in mitigating PV grid-tied related power quality events. Renew Sustain Energy Rev. 2016;56:334\u201346.","journal-title":"Renew Sustain Energy Rev"},{"issue":"2","key":"904_CR9","doi-asserted-by":"publisher","first-page":"824","DOI":"10.1109\/TII.2015.2486379","volume":"12","author":"FA Borges","year":"2015","unstructured":"Borges FA, Fernandes RA, Silva IN, Silva CB. Feature extraction and power quality disturbances classification using smart meters signals. IEEE Trans Ind Inform. 2015;12(2):824\u201333.","journal-title":"IEEE Trans Ind Inform"},{"issue":"15","key":"904_CR10","doi-asserted-by":"publisher","first-page":"2382","DOI":"10.1049\/iet-gtd.2015.0556","volume":"9","author":"S Elphick","year":"2015","unstructured":"Elphick S, Smith V, Gosbell V, Perera S, Ciufo P, Drury G. Characteristics of power quality disturbances in Australia: voltage dips at low-voltage sites. IET Gener Transm Distrib. 2015;9(15):2382\u20138.","journal-title":"IET Gener Transm Distrib"},{"key":"904_CR11","doi-asserted-by":"crossref","unstructured":"R. Igual, C. Medrano, F. J. Arcega, and G. Mantescu, \u201cIntegral mathematical model of power quality disturbances,\u201d in 18th International Conference on Harmonics and Quality of Power (ICHQP) 2018, pp. 1\u20136.","DOI":"10.1109\/ICHQP.2018.8378902"},{"key":"904_CR12","doi-asserted-by":"publisher","first-page":"495","DOI":"10.1016\/j.rser.2014.08.070","volume":"41","author":"OP Mahela","year":"2015","unstructured":"Mahela OP, Shaik AG, Gupta N. A critical review of detection and classification of power quality events. Renew Sustain Energy Rev. 2015;41:495\u2013505.","journal-title":"Renew Sustain Energy Rev"},{"key":"904_CR13","doi-asserted-by":"publisher","first-page":"1650","DOI":"10.1016\/j.rser.2015.07.068","volume":"51","author":"S Khokhar","year":"2015","unstructured":"Khokhar S, Zin AABM, Mokhtar ASB, Pesaran M. A comprehensive overview on signal processing and artificial intelligence techniques applications in classification of power quality disturbances. Renew Sustain Energy Rev. 2015;51:1650\u201363.","journal-title":"Renew Sustain Energy Rev"},{"key":"904_CR14","doi-asserted-by":"publisher","first-page":"16816","DOI":"10.1109\/ACCESS.2018.2814981","volume":"6","author":"E Hossain","year":"2018","unstructured":"Hossain E, T\u00fcr MR, Padmanaban S, Ay S, Khan I. Analysis and mitigation of power quality issues in distributed generation systems using custom power devices. IEEE Access. 2018;6:16816\u201333. https:\/\/doi.org\/10.1109\/ACCESS.2018.2814981.","journal-title":"IEEE Access"},{"key":"904_CR15","unstructured":"V. K. Ingle and J. G. Proakis, Digital signal processing using matlab: a problem solving companion. Cengage Learning, Boston, MA, 2016."},{"issue":"106462","key":"904_CR16","first-page":"2019","volume":"79","author":"SM Qaisar","year":"2019","unstructured":"Qaisar SM. Efficient mobile systems based on adaptive rate signal processing. Comput Electr Eng. 2019;79(106462):2019.","journal-title":"Comput Electr Eng"},{"issue":"1","key":"904_CR17","first-page":"35","volume":"9","author":"S Mina Qaisar","year":"2018","unstructured":"Mina Qaisar S, Sidiya D, Akbar M, Subasi A. An event-driven multiple objects surveillance system. Int J Electr Comput Eng Syst. 2018;9(1):35\u201344.","journal-title":"Int J Electr Comput Eng Syst"},{"key":"904_CR18","unstructured":"S. M. Qaisar, L. Fesquet, and M. Renaudin, \u201cEffective resolution of an adaptive rate ADC,\u201d in 8th International Conference on Sampling Theory and Applications (SAMPTA\u201909), Marseille, France, 2009."},{"issue":"2","key":"904_CR19","doi-asserted-by":"publisher","first-page":"623","DOI":"10.1007\/s13246-020-00863-6","volume":"43","author":"SM Qaisar","year":"2020","unstructured":"Qaisar SM, Subasi A. Cloud-based ECG monitoring using event-driven ECG acquisition and machine learning techniques. Phys Eng Sci Med. 2020;43(2):623\u201334.","journal-title":"Phys Eng Sci Med"},{"issue":"5","key":"904_CR20","doi-asserted-by":"publisher","first-page":"e0252104","DOI":"10.1371\/journal.pone.0252104","volume":"16","author":"S Mian Qaisar","year":"2021","unstructured":"Mian Qaisar S. Signal-piloted processing and machine learning based efficient power quality disturbances recognition. PLoS ONE. 2021;16(5):e0252104.","journal-title":"PLoS ONE"},{"key":"904_CR21","doi-asserted-by":"publisher","unstructured":"S. M. Qaisar and S. F. Hussain, \u201cAn effective arrhythmia classification via ECG signal subsampling and mutual information based subbands statistical features selection,\u201d J. Ambient Intell. Humaniz. Comput. 2021. https:\/\/doi.org\/10.1007\/s12652-021-03275-w.","DOI":"10.1007\/s12652-021-03275-w"},{"key":"904_CR22","unstructured":"H. Ian, E. Frank, M. Hall, and J. Christopher, \u201cData mining: Practical machine learning tools and techniques\u2014Part II: More advanced machine learning schemes.\u201d Morgan Kaufmann, Burlington, MA, 2017."},{"issue":"14","key":"904_CR23","doi-asserted-by":"publisher","first-page":"3832","DOI":"10.1109\/TSP.2019.2919415","volume":"67","author":"BA Moser","year":"2019","unstructured":"Moser BA, Lunglmayr M. On quasi-isometry of threshold-based sampling. IEEE Trans Signal Process. 2019;67(14):3832\u201341.","journal-title":"IEEE Trans Signal Process"},{"key":"904_CR24","unstructured":"R. Gandhi, \u201cSupport Vector Machine \u2014 Introduction to Machine Learning Algorithms,\u201d Medium, Jul. 05, 2018. https:\/\/towardsdatascience.com\/support-vector-machine-introduction-to-machine-learning-algorithms-934a444fca47 Accessed Apr 08, 2020."},{"key":"904_CR25","first-page":"1","volume":"36","author":"S Suthaharan","year":"2016","unstructured":"Suthaharan S. Machine learning models and algorithms for big data classification. Integr Ser Inf Syst. 2016;36:1\u201312.","journal-title":"Integr Ser Inf Syst"},{"key":"904_CR26","doi-asserted-by":"crossref","unstructured":"A. Sabo and S. M. Qaisar, \u201cThe event-driven power efficient wireless sensor nodes for monitoring of insects and health of plants,\u201d in 3rd International Conference on Signal and Image Processing (ICSIP), 2018, pp. 478\u2013483.","DOI":"10.1109\/SIPROCESS.2018.8600505"},{"issue":"21","key":"904_CR27","doi-asserted-by":"publisher","first-page":"5600","DOI":"10.3390\/en13215600","volume":"13","author":"S Mian Qaisar","year":"2020","unstructured":"Mian Qaisar S. Event-driven coulomb counting for effective online approximation of Li-ion battery state of charge. Energies. 2020;13(21):5600.","journal-title":"Energies"},{"issue":"4","key":"904_CR28","doi-asserted-by":"publisher","first-page":"114","DOI":"10.1049\/htl.2019.0116","volume":"7","author":"SM Qaisar","year":"2020","unstructured":"Qaisar SM. Baseline wander and power-line interference elimination of ECG signals using efficient signal-piloted filtering. Healthc Technol Lett. 2020;7(4):114\u20138.","journal-title":"Healthc Technol Lett"}],"container-title":["SN Computer Science"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s42979-021-00904-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s42979-021-00904-1\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s42979-021-00904-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,9,10]],"date-time":"2024-09-10T20:49:32Z","timestamp":1726001372000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s42979-021-00904-1"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,10,26]]},"references-count":28,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2022,1]]}},"alternative-id":["904"],"URL":"https:\/\/doi.org\/10.1007\/s42979-021-00904-1","relation":{},"ISSN":["2662-995X","2661-8907"],"issn-type":[{"value":"2662-995X","type":"print"},{"value":"2661-8907","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,10,26]]},"assertion":[{"value":"14 August 2021","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"22 September 2021","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"26 October 2021","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare that they have no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}],"article-number":"14"}}