{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,27]],"date-time":"2025-03-27T02:26:20Z","timestamp":1743042380552,"version":"3.40.3"},"publisher-location":"Singapore","reference-count":22,"publisher":"Springer Nature Singapore","isbn-type":[{"type":"print","value":"9789811684296"},{"type":"electronic","value":"9789811684302"}],"license":[{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"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":[],"published-print":{"date-parts":[[2022]]},"DOI":"10.1007\/978-981-16-8430-2_11","type":"book-chapter","created":{"date-parts":[[2022,1,4]],"date-time":"2022-01-04T18:02:42Z","timestamp":1641319362000},"page":"114-124","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Dynamic Multiple Indicators Matching Processing for Power Load Forecasting System"],"prefix":"10.1007","author":[{"given":"Tiehua","family":"Zhou","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiayu","family":"Hao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Futao","family":"Ma","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ling","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2022,1,4]]},"reference":[{"issue":"1","key":"11_CR1","doi-asserted-by":"publisher","first-page":"012084","DOI":"10.1088\/1742-6596\/1069\/1\/012084","volume":"1069","author":"B Hu","year":"2018","unstructured":"Hu, B., Pang, C., Wang, L., Chu, H., Mao, C.: Big data management and application research in power load forecasting and power transmission and transformation equipment evaluation. J. Phys. Conf. Ser. 1069(1), 012084 (2018)","journal-title":"J. Phys. Conf. Ser."},{"key":"11_CR2","doi-asserted-by":"publisher","first-page":"410","DOI":"10.1016\/j.enpol.2018.04.060","volume":"119","author":"JP Carvallo","year":"2018","unstructured":"Carvallo, J.P., Larsen, P.H., Sanstad, A.H., Goldman, C.A.: Long term load forecasting accuracy in electric utility integrated resource planning. Energy Policy 119, 410\u2013422 (2018)","journal-title":"Energy Policy"},{"issue":"4","key":"11_CR3","doi-asserted-by":"publisher","first-page":"614","DOI":"10.1007\/s11431-019-9547-4","volume":"63","author":"W Zhang","year":"2020","unstructured":"Zhang, W., Qin, J., Mei, F., Fu, J., Dai, B., Yu, W.: Short-term power load forecasting using integrated methods based on long short-term memory. Sci. China Technol. Sci. 63(4), 614\u2013624 (2020). https:\/\/doi.org\/10.1007\/s11431-019-9547-4","journal-title":"Sci. China Technol. Sci."},{"key":"11_CR4","doi-asserted-by":"publisher","first-page":"345","DOI":"10.1016\/j.epsr.2014.10.003","volume":"119","author":"N Ding","year":"2015","unstructured":"Ding, N., B\u00e9sanger, Y., Wurtz, F.: Next-day MV\/LV substation load forecaster using time series method. Electric Power Syst. Res. 119, 345\u2013354 (2015)","journal-title":"Electric Power Syst. Res."},{"key":"11_CR5","doi-asserted-by":"publisher","first-page":"1516","DOI":"10.4028\/www.scientific.net\/AMR.960-961.1516","volume":"960","author":"C Chen","year":"2014","unstructured":"Chen, C., Zhou, J.N.: Application of regression analysis in power system load forecasting. Adv. Mater. Res. 960, 1516\u20131522 (2014)","journal-title":"Adv. Mater. Res."},{"key":"11_CR6","doi-asserted-by":"publisher","first-page":"697","DOI":"10.4028\/www.scientific.net\/AMM.734.697","volume":"734","author":"WZ Cai","year":"2015","unstructured":"Cai, W.Z., Wang, D.T., Wang, Y.S., Yang, Y., Gao, Z.L.: Study of short-term wind power forecasting based on adaptive grey prediction method. Appl. Mech. Mater. 734, 697\u2013700 (2015)","journal-title":"Appl. Mech. Mater."},{"key":"11_CR7","doi-asserted-by":"publisher","first-page":"37","DOI":"10.1016\/j.jvcir.2018.10.024","volume":"58","author":"LQ Hu","year":"2019","unstructured":"Hu, L.Q., He, C.F., Cai, Z.Q., Wen, L., Ren, T.: Track circuit fault prediction method based on grey theory and expert system. J. Vis. Commun. Image Represent. 58, 37\u201345 (2019)","journal-title":"J. Vis. Commun. Image Represent."},{"issue":"3","key":"11_CR8","doi-asserted-by":"publisher","first-page":"191","DOI":"10.1080\/21642583.2018.1544947","volume":"6","author":"L Guo","year":"2018","unstructured":"Guo, L., Chen, J., Wu, F., Wang, M.: An electric power generation forecasting method using support vector machine. Syst. Sci. Control Eng. 6(3), 191\u2013199 (2018)","journal-title":"Syst. Sci. Control Eng."},{"issue":"5","key":"11_CR9","first-page":"51","volume":"7","author":"Y Lan","year":"2021","unstructured":"Lan, Y., Xue, L., Liao, X.: Short-term power load forecasting based on RBF neural network. Int. Core J. Eng. 7(5), 51\u201359 (2021)","journal-title":"Int. Core J. Eng."},{"key":"11_CR10","doi-asserted-by":"crossref","unstructured":"Pan, J., Qi, M.: Study on short-term load forecasting of distributed power system based on wavelet theory. In: 2018 10th International Conference on Measuring Technology and Mechatronics Automation (ICMTMA), pp. 170\u2013173 (2018)","DOI":"10.1109\/ICMTMA.2018.00048"},{"key":"11_CR11","doi-asserted-by":"publisher","first-page":"658","DOI":"10.4028\/www.scientific.net\/AMM.575.658","volume":"575","author":"YL Wang","year":"2014","unstructured":"Wang, Y.L., Li, Q.Y.: Application of the improved grey model in power load forecasting. Appl. Mech. Mater. 575, 658\u2013661 (2014)","journal-title":"Appl. Mech. Mater."},{"key":"11_CR12","doi-asserted-by":"publisher","first-page":"272","DOI":"10.1016\/j.energy.2016.04.009","volume":"107","author":"H Zhao","year":"2016","unstructured":"Zhao, H., Guo, S.: An optimized grey model for annual power load forecasting. Energy 107, 272\u2013286 (2016)","journal-title":"Energy"},{"issue":"3","key":"11_CR13","doi-asserted-by":"publisher","first-page":"159","DOI":"10.1007\/s12530-014-9112-2","volume":"5","author":"R Ballini","year":"2014","unstructured":"Ballini, R., Yager, R.R.: OWA filters and forecasting models applied to electric power load time series. Evol. Syst. 5(3), 159\u2013173 (2014). https:\/\/doi.org\/10.1007\/s12530-014-9112-2","journal-title":"Evol. Syst."},{"issue":"3","key":"11_CR14","doi-asserted-by":"publisher","first-page":"345","DOI":"10.1002\/int.22055","volume":"34","author":"S Linares-Mustar\u00f3s","year":"2019","unstructured":"Linares-Mustar\u00f3s, S., Ferrer-Comalat, J.C., Corominas-Coll, D., Merig\u00f3, J.M.: The ordered weighted average in the theory of expertons. Int. J. Intell. Syst. 34(3), 345\u2013365 (2019)","journal-title":"Int. J. Intell. Syst."},{"issue":"17","key":"11_CR15","doi-asserted-by":"publisher","first-page":"5066","DOI":"10.1080\/03610926.2014.936560","volume":"45","author":"CH Ho","year":"2016","unstructured":"Ho, C.H.: Forecasting a point process with an ARIMA model. Commun. Stat. Theory Methods 45(17), 5066\u20135076 (2016)","journal-title":"Commun. Stat. Theory Methods"},{"issue":"2","key":"11_CR16","doi-asserted-by":"publisher","first-page":"443","DOI":"10.3390\/en13020443","volume":"13","author":"S Park","year":"2020","unstructured":"Park, S., Moon, J., Jung, S., Rho, S., Baik, S.W., Hwang, E.: A two-stage industrial load forecasting scheme for day-ahead combined cooling, heating and power scheduling. Energies 13(2), 443 (2020)","journal-title":"Energies"},{"issue":"6","key":"11_CR17","doi-asserted-by":"publisher","first-page":"1678","DOI":"10.1002\/cta.2928","volume":"49","author":"V Veeramsetty","year":"2020","unstructured":"Veeramsetty, V., Chandra, D.R., Salkuti, S.R.: Short-term electric power load forecasting using factor analysis and long short-term memory for smart cities. Int. J. Circuit Theory Appl. 49(6), 1678\u20131703 (2020)","journal-title":"Int. J. Circuit Theory Appl."},{"issue":"1","key":"11_CR18","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1080\/01611194.2015.1126660","volume":"41","author":"R Vobbilisetty","year":"2017","unstructured":"Vobbilisetty, R., Di Troia, F., Low, R.M., Visaggio, C.A., Stamp, M.: Classic cryptanalysis using hidden Markov models. Cryptologia 41(1), 1\u201328 (2017)","journal-title":"Cryptologia"},{"issue":"6","key":"11_CR19","doi-asserted-by":"publisher","first-page":"563","DOI":"10.1016\/j.orl.2018.08.008","volume":"46","author":"D Steeneck","year":"2018","unstructured":"Steeneck, D., Eng-Larsson, F.: The Baum-Welch algorithm with limiting distribution constraints. Oper. Res. Lett. 46(6), 563\u2013567 (2018)","journal-title":"Oper. Res. Lett."},{"issue":"11","key":"11_CR20","doi-asserted-by":"publisher","first-page":"1105","DOI":"10.1007\/s00607-017-0557-6","volume":"99","author":"MK Hanif","year":"2017","unstructured":"Hanif, M.K., Zimmermann, K.-H.: Accelerating Viterbi algorithm on graphics processing units. Computing 99(11), 1105\u20131123 (2017). https:\/\/doi.org\/10.1007\/s00607-017-0557-6","journal-title":"Computing"},{"issue":"2","key":"11_CR21","doi-asserted-by":"publisher","first-page":"635","DOI":"10.1007\/s42835-020-00358-0","volume":"15","author":"Q Zhang","year":"2020","unstructured":"Zhang, Q., Zhang, J.: Short-term load forecasting method based on EWT and IDBSCAN. J. Electric. Eng. Technol. 15(2), 635\u2013644 (2020)","journal-title":"J. Electric. Eng. Technol."},{"issue":"3","key":"11_CR22","doi-asserted-by":"publisher","first-page":"467","DOI":"10.1007\/s10470-018-1180-y","volume":"95","author":"K Smagulova","year":"2018","unstructured":"Smagulova, K., Krestinskaya, O., James, A.P.: A memristor-based long short term memory circuit. Analog Integr. Circ. Sig. Process. 95(3), 467\u2013472 (2018). https:\/\/doi.org\/10.1007\/s10470-018-1180-y","journal-title":"Analog Integr. Circ. Sig. Process."}],"container-title":["Lecture Notes in Electrical Engineering","Genetic and Evolutionary Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-16-8430-2_11","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,5,5]],"date-time":"2022-05-05T17:07:07Z","timestamp":1651770427000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-16-8430-2_11"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"ISBN":["9789811684296","9789811684302"],"references-count":22,"URL":"https:\/\/doi.org\/10.1007\/978-981-16-8430-2_11","relation":{},"ISSN":["1876-1100","1876-1119"],"issn-type":[{"type":"print","value":"1876-1100"},{"type":"electronic","value":"1876-1119"}],"subject":[],"published":{"date-parts":[[2022]]},"assertion":[{"value":"4 January 2022","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICGEC","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Genetic and Evolutionary Computing","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Jilin City","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"China","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2021","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"21 October 2021","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"23 October 2021","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"14","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"icgec2021","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}