{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,7]],"date-time":"2026-05-07T15:36:40Z","timestamp":1778168200213,"version":"3.51.4"},"reference-count":75,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Access"],"published-print":{"date-parts":[[2023]]},"DOI":"10.1109\/access.2023.3333895","type":"journal-article","created":{"date-parts":[[2023,11,16]],"date-time":"2023-11-16T19:10:44Z","timestamp":1700161844000},"page":"129449-129466","source":"Crossref","is-referenced-by-count":10,"title":["A Multistage Hybrid Deep Learning Model for Enhanced Solar Tracking"],"prefix":"10.1109","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5961-4830","authenticated-orcid":false,"given":"Mwenge","family":"Mulenga","sequence":"first","affiliation":[{"name":"Business Studies Division, National Institute of Public Administration, Lusaka, Zambia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1171-8336","authenticated-orcid":false,"given":"Musa","family":"Phiri","sequence":"additional","affiliation":[{"name":"School of Engineering and Technology, Mulungushi University, Kabwe, Zambia"}]},{"given":"Luckson","family":"Simukonda","sequence":"additional","affiliation":[{"name":"School of Engineering and Technology, Mulungushi University, Kabwe, Zambia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5842-1452","authenticated-orcid":false,"given":"Fadele A.","family":"Alaba","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Federal College of Education, Zaria, Kaduna, Nigeria"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.3390\/en15062150"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.3390\/en13246623"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1016\/j.renene.2014.07.002"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/access.2023.3306473"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1016\/j.egyr.2022.10.145"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1016\/j.renene.2019.10.117"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1016\/j.jksues.2020.04.004"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/ropec.2016.7830580"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/pecon.2014.7062450"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.3390\/en13030529"},{"key":"ref11","first-page":"1","article-title":"Horizontal axis solar tracking system to enhance efficiency with accuracy test by machine learning","volume-title":"Proc. Int. Conf. Mech., Manuf. Process Eng. (ICMMPE)","author":"Mondal"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1002\/er.5676"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1002\/int.22525"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1155\/2019\/3681031"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1088\/1757-899x\/767\/1\/012052"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.3390\/info14040211"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1016\/j.energy.2020.118403"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.3390\/su15097087"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.3390\/app10175975"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1016\/j.engappai.2022.105786"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1016\/j.energy.2021.122812"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/icngis54955.2022.10079733"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.3390\/technologies11030070"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1016\/j.solener.2023.111803"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2022.09.053"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.3390\/s23020945"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1016\/j.apenergy.2019.113541"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/tste.2019.2897136"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1016\/j.egyai.2021.100060"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1007\/s40095-022-00493-6"},{"key":"ref31","first-page":"257","article-title":"Impact of data normalization on stock index forecasting","volume":"6","author":"Nayak","year":"2014","journal-title":"Int. J. Comput. Inf. Syst. Ind."},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.3390\/fi12110194"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2019.105524"},{"issue":"4","key":"ref34","first-page":"13110","article-title":"Data normalization using median & median absolute deviation (MMAD) based Z-score for robust predictions vs. min-max normalization","volume":"19","author":"Kappal","year":"2019","journal-title":"Lond. J. Res. Sci. Nat. Form."},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1007\/978-981-10-2777-2_7"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/access.2021.3094529"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/access.2021.3050838"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/iiceta54559.2022.9888545"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2014.04.048"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.31593\/ijeat.464210"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.2991\/aer.k.201221.038"},{"key":"ref42","first-page":"8","article-title":"Prototype development for adaptive solar tracking and optimization of data communication protocol","volume-title":"Proc. ASEE North Central Sect. Conf.","author":"Kaul"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/jphotov.2021.3120508"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.3390\/en11123493"},{"issue":"1","key":"ref45","first-page":"8","article-title":"Sun position forecasting using the RNN method\u2014LSTM as a solar cell power control reference","volume":"3","author":"Syahram","journal-title":"J. Electr. Eng. Technol."},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1049\/iet-gtd.2020.0814"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1109\/access.2018.2883330"},{"key":"ref48","volume-title":"Hands-on Machine Learning With Scikit-Learn, Keras, and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems","author":"G\u00e9ron","year":"2019"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4842-4470-8_7"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1016\/j.cose.2020.102115"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1016\/j.dib.2021.106914"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1016\/j.dib.2021.106914"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1016\/j.wace.2017.10.003"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1016\/j.trc.2013.11.011"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1016\/j.energy.2017.01.150"},{"key":"ref56","article-title":"Impact of data normalization on deep neural network for time series forecasting","author":"Bhanja","year":"2018","journal-title":"arXiv:1812.05519"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.21449\/ijate.479404"},{"key":"ref58","doi-asserted-by":"publisher","DOI":"10.46592\/turkager.2020.v01i02.011"},{"key":"ref59","article-title":"Imaging time-series to improve classification and imputation","author":"Wang","year":"2015","journal-title":"arXiv:1506.00327"},{"key":"ref60","doi-asserted-by":"publisher","DOI":"10.1109\/sii.2019.8700425"},{"key":"ref61","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2017.11.027"},{"key":"ref62","doi-asserted-by":"publisher","DOI":"10.1016\/j.procs.2018.05.069"},{"key":"ref63","doi-asserted-by":"publisher","DOI":"10.1016\/j.apenergy.2016.08.108"},{"key":"ref64","doi-asserted-by":"publisher","DOI":"10.1016\/j.enconman.2019.02.018"},{"key":"ref65","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4842-2734-3_1"},{"key":"ref66","doi-asserted-by":"publisher","DOI":"10.1109\/access.2022.3140342"},{"key":"ref67","doi-asserted-by":"publisher","DOI":"10.1016\/j.jhydrol.2020.125188"},{"key":"ref68","doi-asserted-by":"publisher","DOI":"10.1016\/j.enconman.2018.02.012"},{"key":"ref69","doi-asserted-by":"publisher","DOI":"10.1016\/j.atmosenv.2016.10.046"},{"key":"ref70","doi-asserted-by":"publisher","DOI":"10.1029\/2021ms002681"},{"key":"ref71","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2021.11.036"},{"key":"ref72","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0174202"},{"key":"ref73","doi-asserted-by":"publisher","DOI":"10.5194\/gmd-7-1247-2014"},{"key":"ref74","doi-asserted-by":"publisher","DOI":"10.1080\/00949655.2019.1658763"},{"key":"ref75","doi-asserted-by":"publisher","DOI":"10.1016\/j.gsf.2023.101631"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6287639\/10005208\/10320347.pdf?arnumber=10320347","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,1,12]],"date-time":"2024-01-12T01:52:43Z","timestamp":1705024363000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10320347\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"references-count":75,"URL":"https:\/\/doi.org\/10.1109\/access.2023.3333895","relation":{},"ISSN":["2169-3536"],"issn-type":[{"value":"2169-3536","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023]]}}}