{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,9,10]],"date-time":"2024-09-10T17:51:36Z","timestamp":1725990696542},"publisher-location":"Singapore","reference-count":27,"publisher":"Springer Singapore","isbn-type":[{"type":"print","value":"9789811322051"},{"type":"electronic","value":"9789811322068"}],"license":[{"start":{"date-parts":[[2018,1,1]],"date-time":"2018-01-01T00:00:00Z","timestamp":1514764800000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2018,1,1]],"date-time":"2018-01-01T00:00:00Z","timestamp":1514764800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2018,1,1]],"date-time":"2018-01-01T00:00:00Z","timestamp":1514764800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2018]]},"DOI":"10.1007\/978-981-13-2206-8_23","type":"book-chapter","created":{"date-parts":[[2018,9,8]],"date-time":"2018-09-08T06:43:21Z","timestamp":1536389001000},"page":"263-272","update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Method and Evaluation Method of Ultra-Short-Load Forecasting in Power System"],"prefix":"10.1007","author":[{"given":"Jiaxiang","family":"Ou","sequence":"first","affiliation":[]},{"given":"Songling","family":"Li","sequence":"additional","affiliation":[]},{"given":"Junwei","family":"Zhang","sequence":"additional","affiliation":[]},{"given":"Chao","family":"Ding","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2018,9,9]]},"reference":[{"issue":"7","key":"23_CR1","doi-asserted-by":"publisher","first-page":"1678","DOI":"10.1109\/TPAS.1970.292823","volume":"89","author":"J Toyoda","year":"1970","unstructured":"Toyoda, J., Chen, M.S., Inoue, Y.: An application of state estimation to short-term load forecasting, Part I: forecasting modeling. IEEE Trans. Power Appar. Syst. 89(7), 1678\u20131682 (1970)","journal-title":"IEEE Trans. Power Appar. Syst."},{"issue":"8","key":"23_CR2","doi-asserted-by":"publisher","first-page":"3775","DOI":"10.1109\/TPAS.1981.317020","volume":"100","author":"S Vemuri","year":"1981","unstructured":"Vemuri, S., Huang, W.L., Nelson, D.J.: Online algorithms for forecasting hourly loads of an electric utility. IEEE Trans. Power Appar. Syst. 100(8), 3775\u20133784 (1981)","journal-title":"IEEE Trans. Power Appar. Syst."},{"key":"23_CR3","doi-asserted-by":"crossref","unstructured":"Ziegel, E.R.: Time series analysis, forecasting, and control. In: Oakland, California, Holden-Day, 1976, vol. 37(2), pp. 238\u2013242 (1976)","DOI":"10.1080\/00401706.1995.10484323"},{"issue":"6","key":"23_CR4","doi-asserted-by":"publisher","first-page":"315","DOI":"10.1016\/S1474-6670(17)59244-7","volume":"20","author":"S Vemuri","year":"1987","unstructured":"Vemuri, S., Hoveida, B., Mohebbi, S.: Short term load forecasting based on weather load models. IFAC Proc. Vol. 20(6), 315\u2013320 (1987)","journal-title":"IFAC Proc. Vol."},{"key":"23_CR5","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/978-3-642-39593-2_1","volume-title":"Statistical Language and Speech Processing","author":"Y Bengio","year":"2013","unstructured":"Bengio, Y.: Deep learning of representations: looking forward. In: Dediu, A.-H., Mart\u00edn-Vide, C., Mitkov, R., Truthe, B. (eds.) SLSP 2013. LNCS (LNAI), vol. 7978, pp. 1\u201337. Springer, Heidelberg (2013). https:\/\/doi.org\/10.1007\/978-3-642-39593-2_1"},{"issue":"2","key":"23_CR6","doi-asserted-by":"publisher","first-page":"900","DOI":"10.1109\/TPAS.1971.293123","volume":"90","author":"WR Christiaanse","year":"1971","unstructured":"Christiaanse, W.R.: Short-term load forecasting using general exponential smoothing. IEEE Trans. Power Appar. Syst. PAS 90(2), 900\u2013911 (1971)","journal-title":"IEEE Trans. Power Appar. Syst. PAS"},{"key":"23_CR7","doi-asserted-by":"crossref","unstructured":"Sage, A.P., Husa, G.W.: Algorithms for sequential adaptive estimation of prior statistics. In: Adaptive Processes, p. 61 (1969)","DOI":"10.1109\/SAP.1969.269927"},{"issue":"2","key":"23_CR8","doi-asserted-by":"publisher","first-page":"175","DOI":"10.1109\/TAC.1970.1099422","volume":"15","author":"RK Mehra","year":"1969","unstructured":"Mehra, R.K.: On the identification of variances and adaptive Kalman filtering. IEEE Trans. Autom. Control 15(2), 175\u2013184 (1969)","journal-title":"IEEE Trans. Autom. Control"},{"key":"23_CR9","doi-asserted-by":"publisher","first-page":"841","DOI":"10.4028\/www.scientific.net\/AMR.732-733.841","volume":"732\u2013733","author":"AI Khalyasmaa","year":"2013","unstructured":"Khalyasmaa, A.I., Dmitriev, S.A., Kokin, S.E.: Energy information model for power systems monitoring. Adv. Mater. Res. 732\u2013733, 841\u2013847 (2013)","journal-title":"Adv. Mater. Res."},{"key":"23_CR10","doi-asserted-by":"publisher","first-page":"412","DOI":"10.1016\/j.apenergy.2017.01.003","volume":"201","author":"IM Coelho","year":"2017","unstructured":"Coelho, I.M., Coelho, V.N., Luz, E.J.D.S., Ochi, L.S., Guimaraes, F.G., Rios, E.: A GPU deep learning metaheuristic based model for time series forecasting. Appl. Energy 201, 412\u2013418 (2017)","journal-title":"Appl. Energy"},{"key":"23_CR11","doi-asserted-by":"publisher","first-page":"1688","DOI":"10.1016\/j.energy.2016.07.090","volume":"115","author":"A Dedinec","year":"2016","unstructured":"Dedinec, A., Filiposka, S., Dedinec, A., Kocarev, L.: Deep belief network based electricity load forecasting: an analysis of macedonian case. Energy 115, 1688\u20131700 (2016)","journal-title":"Energy"},{"issue":"9","key":"23_CR12","doi-asserted-by":"publisher","first-page":"473","DOI":"10.3103\/S1068371209090016","volume":"80","author":"EG Kazakov","year":"2009","unstructured":"Kazakov, E.G., Kirillov, A.V., Kutsin, V.V., Yasenev, N.D.: Educational process at electric drive and automation of industrial installations department of ustu-upi and its methodical and laboratory support. Russ. Electr. Eng. 80(9), 473\u2013476 (2009)","journal-title":"Russ. Electr. Eng."},{"key":"23_CR13","doi-asserted-by":"publisher","first-page":"222","DOI":"10.1016\/j.apenergy.2017.03.064","volume":"195","author":"C Fan","year":"2017","unstructured":"Fan, C., Xiao, F., Zhao, Y.: A short-term building cooling load prediction method using deep learning algorithms. Appl. Energy 195, 222\u2013233 (2017)","journal-title":"Appl. Energy"},{"key":"23_CR14","doi-asserted-by":"publisher","first-page":"1245","DOI":"10.1016\/j.apenergy.2017.01.043","volume":"190","author":"C Feng","year":"2017","unstructured":"Feng, C., Cui, M., Hodge, B.M., Zhang, J.: A data-driven multi-model methodology with deep feature selection for short-term wind forecasting. Appl. Energy 190, 1245\u20131257 (2017)","journal-title":"Appl. Energy"},{"issue":"10","key":"23_CR15","doi-asserted-by":"publisher","first-page":"46","DOI":"10.1109\/MCOM.2017.1700168","volume":"55","author":"L Li","year":"2017","unstructured":"Li, L., Ota, K., Dong, M.: When weather matters: Iot-based electrical load forecasting for smart grid. IEEE Commun. Mag. 55(10), 46\u201351 (2017)","journal-title":"IEEE Commun. Mag."},{"issue":"2","key":"23_CR16","doi-asserted-by":"publisher","first-page":"246","DOI":"10.1016\/j.asoc.2017.01.015","volume":"54","author":"X Qiu","year":"2017","unstructured":"Qiu, X., Ren, Y., Suganthan, P.N., Amaratunga, G.A.J.: Empirical mode decomposition based ensemble deep learning for load demand time series forecasting. Appl. Soft Comput. 54(2), 246\u2013255 (2017)","journal-title":"Appl. Soft Comput."},{"issue":"4","key":"23_CR17","doi-asserted-by":"publisher","first-page":"366","DOI":"10.1007\/s11633-008-0366-7","volume":"5","author":"H Abusaimeh","year":"2008","unstructured":"Abusaimeh, H., Yang, S.H.: Balancing the power consumption speed in flat and hierarchical WSN. Int. J. Autom. Comput. 5(4), 366\u2013375 (2008)","journal-title":"Int. J. Autom. Comput."},{"key":"23_CR18","doi-asserted-by":"crossref","unstructured":"Ryu, S., Noh, J., Kim, H.: Deep neural network based demand side short term load forecasting. In: IEEE International Conference on Smart Grid Communications, p. 3 (2016)","DOI":"10.3390\/en10010003"},{"issue":"99","key":"23_CR19","first-page":"1","volume":"1","author":"L Wang","year":"2017","unstructured":"Wang, L., Zhang, Z., Chen, J.: Short term electricity price forecasting with stacked denoising autoencoders. IEEE Trans. Power Syst. 1(99), 1 (2017)","journal-title":"IEEE Trans. Power Syst."},{"key":"23_CR20","unstructured":"Chan, E.H.P.: Application of neural network computing in intelligent alarm processing (power systems). In: Power Industry Computer Application Conference, 1989, Conference Papers, pp. 246\u2013251 (2002)"},{"key":"23_CR21","doi-asserted-by":"crossref","unstructured":"Wu, X., Shen, Z., Song, Y.: A novel approach for short term electric load forecasting. In: World Congress on Intelligent Control and Automation, pp. 1999\u20132002 (2016)","DOI":"10.1109\/WCICA.2016.7578284"},{"issue":"5","key":"23_CR22","doi-asserted-by":"publisher","first-page":"1765","DOI":"10.1016\/j.ymssp.2010.11.021","volume":"25","author":"EPD Moura","year":"2011","unstructured":"Moura, E.P.D., Souto, C.R., Silva, A.A., Irm\u00e3o, M.A.S.: Evaluation of principal component analysis and neural network performance for bearing fault diagnosis from vibration signal processed by RS and DF analyses. Mech. Syst. Signal Process. 25(5), 1765\u20131772 (2011)","journal-title":"Mech. Syst. Signal Process."},{"key":"23_CR23","doi-asserted-by":"crossref","unstructured":"Vaitheeswaran, N., Balasubramanian, R.: Stochastic model for optimal declaration of day ahead station availability in power pools in India. In: Power India Conference, p. 5 (2006)","DOI":"10.1109\/POWERI.2006.1632553"},{"key":"23_CR24","doi-asserted-by":"crossref","unstructured":"Jain, A., Balasubramanian, R., Tripathy, S.C., Singh, B.N.: Power system topological observability analysis using artificial neural networks. In: Power Engineering Society General Meeting, pp. 497\u2013502 (2005)","DOI":"10.1109\/PES.2006.1709368"},{"issue":"5","key":"23_CR25","doi-asserted-by":"publisher","first-page":"1455","DOI":"10.1016\/j.egypro.2012.01.229","volume":"16","author":"H Nie","year":"2012","unstructured":"Nie, H., Liu, G., Liu, X., Wang, Y.: Hybrid of arima and SVMs for short term load forecasting. Energy Procedia 16(5), 1455\u20131460 (2012)","journal-title":"Energy Procedia"},{"issue":"2","key":"23_CR26","doi-asserted-by":"publisher","first-page":"513","DOI":"10.1109\/TSMCB.2011.2168604","volume":"42","author":"GB Huang","year":"2012","unstructured":"Huang, G.B., Zhou, H., Ding, X., Zhang, R.: Extreme learning machine for regression and multiclass classification. IEEE Trans. Syst. Man Cybern. B Cybern. 42(2), 513\u2013529 (2012)","journal-title":"IEEE Trans. Syst. Man Cybern. B Cybern."},{"issue":"1","key":"23_CR27","doi-asserted-by":"publisher","first-page":"9","DOI":"10.1007\/s00521-013-1537-1","volume":"27","author":"NA Shrivastava","year":"2016","unstructured":"Shrivastava, N.A., Panigrahi, B.K., Lim, M.H.: Electricity price classification using extreme learning machines. Neural Comput. Appl. 27(1), 9\u201318 (2016)","journal-title":"Neural Comput. Appl."}],"container-title":["Communications in Computer and Information Science","Data Science"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-13-2206-8_23","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,12]],"date-time":"2024-03-12T09:08:26Z","timestamp":1710234506000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-13-2206-8_23"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018]]},"ISBN":["9789811322051","9789811322068"],"references-count":27,"URL":"https:\/\/doi.org\/10.1007\/978-981-13-2206-8_23","relation":{},"ISSN":["1865-0929","1865-0937"],"issn-type":[{"type":"print","value":"1865-0929"},{"type":"electronic","value":"1865-0937"}],"subject":[],"published":{"date-parts":[[2018]]},"assertion":[{"value":"9 September 2018","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}}]}}