{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,4,17]],"date-time":"2025-04-17T14:09:51Z","timestamp":1744898991252,"version":"3.40.3"},"publisher-location":"Cham","reference-count":21,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783319572635"},{"type":"electronic","value":"9783319572642"}],"license":[{"start":{"date-parts":[[2017,1,1]],"date-time":"2017-01-01T00:00:00Z","timestamp":1483228800000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2017]]},"DOI":"10.1007\/978-3-319-57264-2_26","type":"book-chapter","created":{"date-parts":[[2017,4,6]],"date-time":"2017-04-06T23:01:15Z","timestamp":1491519675000},"page":"254-263","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Machine Learning Approaches to Electricity Consumption Forecasting in Automated Metering Infrastructure (AMI) Systems: An Empirical Study"],"prefix":"10.1007","author":[{"given":"A.","family":"Jayanth Balaji","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"D. S.","family":"Harish Ram","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Binoy B.","family":"Nair","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2017,4,7]]},"reference":[{"key":"26_CR1","doi-asserted-by":"publisher","first-page":"461","DOI":"10.1016\/j.rser.2013.10.022","volume":"30","author":"P Siano","year":"2014","unstructured":"Siano, P.: Demand response and smart gridsA survey. Renew. Sustain. Energy Rev. 30, 461\u2013478 (2014)","journal-title":"Renew. Sustain. Energy Rev."},{"key":"26_CR2","series-title":"Advances in Intelligent Systems and Computing","doi-asserted-by":"publisher","first-page":"165","DOI":"10.1007\/978-3-319-33389-2_16","volume-title":"Automation Control Theory Perspectives in Intelligent Systems","author":"A Jayanth Balaji","year":"2016","unstructured":"Jayanth Balaji, A., Harish Ram, D.S., Nair, B.B.: Modeling of consumption data for forecasting in automated metering infrastructure (AMI) systems. In: Silhavy, R., Senkerik, R., Oplatkova, Z.K., Silhavy, P., Prokopova, Z. (eds.) Automation Control Theory Perspectives in Intelligent Systems. AISC, vol. 466, pp. 165\u2013173. Springer, Cham (2016). doi:\n                  10.1007\/978-3-319-33389-2_16"},{"issue":"5","key":"26_CR3","doi-asserted-by":"publisher","first-page":"68","DOI":"10.1109\/MSP.2012.2186531","volume":"29","author":"S Chan","year":"2012","unstructured":"Chan, S., et al.: Load\/Price forecasting and managing demand response for smart grids: methodologies and challenges. IEEE Sig. Process. Mag. 29(5), 68\u201385 (2012)","journal-title":"IEEE Sig. Process. Mag."},{"key":"26_CR4","doi-asserted-by":"crossref","unstructured":"Zhao, H., Tang, Z.: The review of demand side management and load forecasting in smart grid. In: 2016 12th World Congress on Intelligent Control and Automation (WCICA) (2016)","DOI":"10.1109\/WCICA.2016.7578513"},{"issue":"1","key":"26_CR5","doi-asserted-by":"publisher","first-page":"349","DOI":"10.1109\/TSG.2013.2261829","volume":"5","author":"M Tasdighi","year":"2014","unstructured":"Tasdighi, M., et al.: Residential microgrid scheduling based on smart meters data and temperature dependent thermal load modeling. IEEE Trans. Smart Grid 5(1), 349\u2013357 (2014)","journal-title":"IEEE Trans. Smart Grid"},{"issue":"1","key":"26_CR6","doi-asserted-by":"publisher","first-page":"456","DOI":"10.1109\/TSG.2013.2274373","volume":"5","author":"T Hong","year":"2014","unstructured":"Hong, T., et al.: Long term probabilistic load forecasting and normalization with hourly information. IEEE Trans. Smart Grid 5(1), 456\u2013462 (2014)","journal-title":"IEEE Trans. Smart Grid"},{"issue":"1","key":"26_CR7","doi-asserted-by":"publisher","first-page":"420","DOI":"10.1109\/TSG.2013.2278477","volume":"5","author":"J Kwac","year":"2014","unstructured":"Kwac, J., et al.: Household energy consumption segmentation using hourly data. IEEE Trans. Smart Grid 5(1), 420\u2013430 (2014)","journal-title":"IEEE Trans. Smart Grid"},{"key":"26_CR8","unstructured":"ISSDA. \n                  http:\/\/www.ucd.ie\/issda\/data\/commissionforenergyregulationcer\/"},{"key":"26_CR9","doi-asserted-by":"crossref","unstructured":"Hodrick, R., Prescott, E.: Postwar U.S. business cycles. In: Real Business Cycles A Reader, pp. 593\u2013608 (1998)","DOI":"10.4324\/9780203070710.pt8"},{"key":"26_CR10","doi-asserted-by":"publisher","first-page":"20","DOI":"10.1016\/j.eswa.2016.11.002","volume":"70","author":"BB Nair","year":"2017","unstructured":"Nair, B.B., et al.: Clustering stock price time series data to generate stock trading recommendations: an empirical study. Expert Syst. Appl. 70, 20\u201336 (2017)","journal-title":"Expert Syst. Appl."},{"issue":"3","key":"26_CR11","first-page":"243","volume":"9","author":"BB Nair","year":"2015","unstructured":"Nair, B.B., Mohandas, V.: An intelligent recommender system for stock trading. Intell. Decis. Technol. IDT 9(3), 243\u2013269 (2015)","journal-title":"Intell. Decis. Technol. IDT"},{"issue":"2","key":"26_CR12","first-page":"99","volume":"9","author":"BB Nair","year":"2015","unstructured":"Nair, B.B., Mohandas, V.: Artificial intelligence applications in financial forecasting-a survey and some empirical results. Intell. Decis. Technol. IDT 9(2), 99\u2013140 (2015)","journal-title":"Intell. Decis. Technol. IDT"},{"key":"26_CR13","doi-asserted-by":"publisher","first-page":"2","DOI":"10.1177\/2158244015579941","volume":"5","author":"BB Nair","year":"2015","unstructured":"Nair, B.B., et al.: A stock trading recommender system based on temporal association rule mining. SAGE Open 5, 2 (2015)","journal-title":"SAGE Open"},{"key":"26_CR14","unstructured":"Huang, G.-B., et al.: Extreme learning machine: a new learning scheme of feedforward neural networks. In: 2004 IEEE International Joint Conference on Neural Networks (IEEE Cat. No. 04CH37541)"},{"issue":"1\u20133","key":"26_CR15","doi-asserted-by":"publisher","first-page":"489","DOI":"10.1016\/j.neucom.2005.12.126","volume":"70","author":"G-B Huang","year":"2006","unstructured":"Huang, G.-B., et al.: Extreme learning machine: theory and applications. Neurocomputing 70(1\u20133), 489\u2013501 (2006)","journal-title":"Neurocomputing"},{"issue":"2","key":"26_CR16","doi-asserted-by":"publisher","first-page":"513","DOI":"10.1109\/TSMCB.2011.2168604","volume":"42","author":"G-B Huang","year":"2012","unstructured":"Huang, G.-B., et al.: Extreme learning machine for regression and multiclass classification. IEEE Trans. Syst. Man Cybern. Part B (Cybern.) 42(2), 513\u2013529 (2012)","journal-title":"IEEE Trans. Syst. Man Cybern. Part B (Cybern.)"},{"issue":"3","key":"26_CR17","doi-asserted-by":"publisher","first-page":"376","DOI":"10.1007\/s12559-014-9255-2","volume":"6","author":"G-B Huang","year":"2014","unstructured":"Huang, G.-B.: An insight into extreme learning machines: random neurons, random features and Kernels. Cogn. Comput. 6(3), 376\u2013390 (2014)","journal-title":"Cogn. Comput."},{"issue":"7","key":"26_CR18","doi-asserted-by":"publisher","first-page":"1033","DOI":"10.1016\/S0893-6080(09)80013-0","volume":"6","author":"DF Specht","year":"1993","unstructured":"Specht, D.F.: The general regression neural network-Rediscovered. Neural Netw. 6(7), 1033\u20131034 (1993)","journal-title":"Neural Netw."},{"issue":"2","key":"26_CR19","first-page":"123","volume":"24","author":"L Breiman","year":"1996","unstructured":"Breiman, L.: Bagging predictors. Mach. Learn. 24(2), 123\u2013140 (1996)","journal-title":"Mach. Learn."},{"key":"26_CR20","unstructured":"Israel, G.D.: Determining sample size. University of Florida Cooperative Extension Service, Institute of Food and Agriculture Sciences, EDIS (1992)"},{"issue":"3","key":"26_CR21","doi-asserted-by":"publisher","first-page":"443","DOI":"10.1016\/j.ijforecast.2006.01.001","volume":"22","author":"JGD Gooijer","year":"2006","unstructured":"Gooijer, J.G.D., Hyndman, R.J.: 25 years of time series forecasting. Int. J. Forecast. 22(3), 443\u2013473 (2006)","journal-title":"Int. J. Forecast."}],"container-title":["Advances in Intelligent Systems and Computing","Cybernetics and Mathematics Applications in Intelligent Systems"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-319-57264-2_26","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,5,18]],"date-time":"2019-05-18T00:42:25Z","timestamp":1558140145000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-319-57264-2_26"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017]]},"ISBN":["9783319572635","9783319572642"],"references-count":21,"URL":"https:\/\/doi.org\/10.1007\/978-3-319-57264-2_26","relation":{},"ISSN":["2194-5357","2194-5365"],"issn-type":[{"type":"print","value":"2194-5357"},{"type":"electronic","value":"2194-5365"}],"subject":[],"published":{"date-parts":[[2017]]},"assertion":[{"value":"7 April 2017","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"CSOC","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Computer Science On-line Conference","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Prague","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Czech Republic","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2017","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"26 April 2017","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"29 April 2017","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"6","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"csolc2017","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.openpublish.eu\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}