{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,22]],"date-time":"2026-04-22T18:02:11Z","timestamp":1776880931049,"version":"3.51.2"},"publisher-location":"Cham","reference-count":31,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783030150341","type":"print"},{"value":"9783030150358","type":"electronic"}],"license":[{"start":{"date-parts":[[2019,1,1]],"date-time":"2019-01-01T00:00:00Z","timestamp":1546300800000},"content-version":"tdm","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":[[2019]]},"DOI":"10.1007\/978-3-030-15035-8_108","type":"book-chapter","created":{"date-parts":[[2019,3,14]],"date-time":"2019-03-14T08:30:46Z","timestamp":1552552246000},"page":"1120-1131","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":68,"title":["Short Term Load Forecasting Using XGBoost"],"prefix":"10.1007","author":[{"given":"Raza Abid","family":"Abbasi","sequence":"first","affiliation":[]},{"given":"Nadeem","family":"Javaid","sequence":"additional","affiliation":[]},{"given":"Muhammad Nauman Javid","family":"Ghuman","sequence":"additional","affiliation":[]},{"given":"Zahoor Ali","family":"Khan","sequence":"additional","affiliation":[]},{"given":"Shujat","family":"Ur Rehman","sequence":"additional","affiliation":[]},{"family":"Amanullah","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2019,3,15]]},"reference":[{"key":"108_CR1","doi-asserted-by":"publisher","first-page":"158","DOI":"10.1016\/j.epsr.2014.05.008","volume":"116","author":"T Mathaba","year":"2014","unstructured":"Mathaba, T., Xia, X., Zhang, J.: Analysing the economic benefit of electricity price forecast in industrial load scheduling. Electr. Power Syst. Res. 116, 158\u2013165 (2014)","journal-title":"Electr. Power Syst. Res."},{"key":"108_CR2","doi-asserted-by":"crossref","unstructured":"Sarada, K., Bapiraju, V.: Comparison of day-ahead price forecasting in energy market using Neural Network and Genetic Algorithm. In: Proceeding of the International Conference on Smart Electric Grid, pp. 1\u20135 (2014)","DOI":"10.1109\/ISEG.2014.7005607"},{"issue":"5","key":"108_CR3","doi-asserted-by":"publisher","first-page":"2165","DOI":"10.1016\/j.enconman.2010.10.047","volume":"52","author":"M Shafie-Khah","year":"2011","unstructured":"Shafie-Khah, M., Moghaddam, M.P., Sheikh-El-Eslami, M.: Price forecasting of day-ahead electricity markets using a hybrid forecast method. Energy Convers. Manag. 52(5), 2165\u20132169 (2011)","journal-title":"Energy Convers. Manag."},{"issue":"2","key":"108_CR4","doi-asserted-by":"publisher","first-page":"867","DOI":"10.1109\/TPWRS.2005.846044","volume":"20","author":"RC Garcia","year":"2005","unstructured":"Garcia, R.C., Contreras, J., Van Akkeren, M., Garcia, J.B.C.: A GARCH forecasting model to predict day-ahead electricity prices. IEEE Trans. Power Syst. 20(2), 867\u2013874 (2005)","journal-title":"IEEE Trans. Power Syst."},{"key":"108_CR5","doi-asserted-by":"crossref","unstructured":"Shahidehpour, M., Yamin, H., Li, Z.: Market overview in electric power systems. In: Market Operations in Electric Power Systems, pp. 1\u201320. Wiley, New York (2002)","DOI":"10.1002\/047122412X"},{"issue":"1","key":"108_CR6","doi-asserted-by":"publisher","first-page":"98","DOI":"10.1016\/j.physa.2007.03.050","volume":"382","author":"G Ci-wei","year":"2007","unstructured":"Ci-wei, G., Bompard, E., Napoli, R., Cheng, H.: Price forecast in the competitive electricity market by support vector machine. Phys. A: Stat. Mech. Appl. 382(1), 98\u2013113 (2007)","journal-title":"Phys. A: Stat. Mech. Appl."},{"issue":"2","key":"108_CR7","doi-asserted-by":"publisher","first-page":"278","DOI":"10.1049\/iet-rpg.2016.0364","volume":"11","author":"Y Cai","year":"2017","unstructured":"Cai, Y., Lin, J., Wan, C., Song, Y.: A stochastic Bi-level trading model for an active distribution company with distributed generation and interruptible loads. IET Renew. Power Gener. 11(2), 278\u2013288 (2017)","journal-title":"IET Renew. Power Gener."},{"issue":"4","key":"108_CR8","doi-asserted-by":"publisher","first-page":"1030","DOI":"10.1016\/j.ijforecast.2014.08.008","volume":"30","author":"R Weron","year":"2014","unstructured":"Weron, R.: Electricity price forecasting: a review of the state-of-the-art with a look into the future. Int. J. Forecast. 30(4), 1030\u20131081 (2014)","journal-title":"Int. J. Forecast."},{"issue":"2","key":"108_CR9","doi-asserted-by":"publisher","first-page":"114","DOI":"10.5370\/JICEE.2014.4.2.114","volume":"4","author":"L Hu","year":"2014","unstructured":"Hu, L., Taylor, G.: A novel hybrid technique for short-term electricity price forecasting in UK electricity markets. J. Int. Counc. Electr. Eng. 4(2), 114\u2013120 (2014)","journal-title":"J. Int. Counc. Electr. Eng."},{"issue":"5","key":"108_CR10","doi-asserted-by":"publisher","first-page":"626","DOI":"10.1002\/er.3067","volume":"38","author":"S Voronin","year":"2014","unstructured":"Voronin, S., Partanen, J.: Forecasting electricity price and demand using a hybrid approach based on wavelet transform, ARIMA and neural networks. Int. J. Energy Res. 38(5), 626\u2013637 (2014)","journal-title":"Int. J. Energy Res."},{"key":"108_CR11","doi-asserted-by":"publisher","first-page":"298","DOI":"10.1016\/j.enconman.2014.10.003","volume":"89","author":"P Kou","year":"2015","unstructured":"Kou, P., Liang, D., Gao, L., Lou, J.: Probabilistic electricity price forecasting with variational heteroscedastic Gaussian process and active learning. Energy Convers. Manag. 89, 298\u2013308 (2015)","journal-title":"Energy Convers. Manag."},{"key":"108_CR12","doi-asserted-by":"publisher","first-page":"41","DOI":"10.1016\/j.ijepes.2013.08.023","volume":"55","author":"NA Shrivastava","year":"2014","unstructured":"Shrivastava, N.A., Panigrahi, B.K.: A hybrid wavelet-ELM based short term price forecasting for electricity markets. Int. J. Electr. Power Energy Syst. 55, 41\u201350 (2014)","journal-title":"Int. J. Electr. Power Energy Syst."},{"key":"108_CR13","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.physa.2015.01.012","volume":"425","author":"K He","year":"2015","unstructured":"He, K., Xu, Y., Zou, Y., Tang, L.: Electricity price forecasts using a curvelet denoising based approach. Phys. A: Stat. Mech. Appl. 425, 1\u20139 (2015)","journal-title":"Phys. A: Stat. Mech. Appl."},{"issue":"1","key":"108_CR14","doi-asserted-by":"publisher","first-page":"463","DOI":"10.1109\/TSG.2013.2274465","volume":"5","author":"C Wan","year":"2014","unstructured":"Wan, C., Xu, Z., Wang, Y., Dong, Z.Y., Wong, K.P.: A hybrid approach for probabilistic forecasting of electricity price. IEEE Trans. Smart Grid 5(1), 463\u2013470 (2014)","journal-title":"IEEE Trans. Smart Grid"},{"issue":"1","key":"108_CR15","doi-asserted-by":"publisher","first-page":"817","DOI":"10.1109\/TPWRS.2016.2550867","volume":"32","author":"C Wan","year":"2017","unstructured":"Wan, C., Niu, M., Song, Y., Xu, Z.: Pareto optimal prediction intervals of electricity price. IEEE Trans. Power Syst. 32(1), 817\u2013819 (2017)","journal-title":"IEEE Trans. Power Syst."},{"issue":"2","key":"108_CR16","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1109\/tsg.2015.2437877","volume":"8","author":"B Liu","year":"2017","unstructured":"Liu, B., Nowotarski, J., Hong, T., Weron, R.: Probabilistic load forecasting via quantile regression averaging on sister forecasts. IEEE Trans. Smart Grid 8(2), 1 (2017). \n                    https:\/\/doi.org\/10.1109\/tsg.2015.2437877","journal-title":"IEEE Trans. Smart Grid"},{"key":"108_CR17","doi-asserted-by":"publisher","first-page":"585","DOI":"10.1016\/j.ijforecast.2015.09.006","volume":"32","author":"P Wanga","year":"2016","unstructured":"Wanga, P., Liu, B., Hongb, T.: Electric load forecasting with recency effect: a big data approach. Int. J. Forecast. 32, 585\u2013597 (2016)","journal-title":"Int. J. Forecast."},{"key":"108_CR18","doi-asserted-by":"publisher","first-page":"247","DOI":"10.1016\/j.autcon.2016.01.002","volume":"72","author":"J-S Chou","year":"2016","unstructured":"Chou, J.-S., Ngo, N.-T.: Smart grid data analytics framework for increasing energy savings in residential buildings. Autom. Constr. 72, 247\u2013257 (2016)","journal-title":"Autom. Constr."},{"key":"108_CR19","unstructured":"Ludwig, N., Feuerriegel, S., Neumann, D.: Putting big data analytics to work: feature selection for forecasting electricity prices using the LASSO and random forests. ISSN 1246-0125 (Print) 2116-7052"},{"key":"108_CR20","doi-asserted-by":"publisher","first-page":"386","DOI":"10.1016\/j.apenergy.2018.02.069","volume":"221","author":"J Lago","year":"2018","unstructured":"Lago, J., De Ridder, F., De Schutter, B.: Forecasting spot electricity prices: deep learning approaches and empirical comparison of traditional algorithms. Appl. Energy 221, 386\u2013405 (2018)","journal-title":"Appl. Energy"},{"issue":"4","key":"108_CR21","doi-asserted-by":"publisher","first-page":"2673","DOI":"10.1109\/TPWRS.2016.2628873","volume":"32","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. 32(4), 2673\u20132681 (2017)","journal-title":"IEEE Trans. Power Syst."},{"issue":"1","key":"108_CR22","doi-asserted-by":"publisher","first-page":"890","DOI":"10.1016\/j.apenergy.2017.11.098","volume":"211","author":"J Lagoa","year":"2018","unstructured":"Lagoa, J., De Ridder, F., Vrancx, P., De Schutter, B.: Forecasting day-ahead electricity prices in Europe: the importance of considering market integration. Appl. Energy 211(1), 890\u2013903 (2018)","journal-title":"Appl. Energy"},{"key":"108_CR23","doi-asserted-by":"publisher","first-page":"227","DOI":"10.1016\/j.eneco.2015.05.014","volume":"50","author":"E Raviv","year":"2015","unstructured":"Raviv, E., Bouwman, K.E., van Dijk, D.: Forecasting day-ahead electricity prices: utilizing hourly prices. Energy Econ. 50, 227\u2013239 (2015)","journal-title":"Energy Econ."},{"issue":"15","key":"108_CR24","doi-asserted-by":"publisher","first-page":"524","DOI":"10.1016\/j.energy.2015.01.063","volume":"82","author":"L Xiao","year":"2015","unstructured":"Xiao, L., Jianzhou Wang, R., Hou, J.W.: A combined model based on data pre-analysis and weight coefficients optimization for electrical load forecasting. Energy 82(15), 524\u2013549 (2015)","journal-title":"Energy"},{"key":"108_CR25","doi-asserted-by":"publisher","first-page":"452","DOI":"10.3390\/en11020452","volume":"11","author":"S Singh","year":"2018","unstructured":"Singh, S., Yassine, A.: Big data mining of energy time series for behavioral analytics and energy consumption forecasting. Energies 11, 452 (2018)","journal-title":"Energies"},{"key":"108_CR26","doi-asserted-by":"crossref","unstructured":"Moon, J., Kim, K.-H., Kim, Y., Hwang, E.: A short-term electric load forecasting scheme using 2-stage predictive analytics. In: 2018 IEEE International Conference on Big Data and Smart Computing (2018)","DOI":"10.1109\/BigComp.2018.00040"},{"issue":"1","key":"108_CR27","doi-asserted-by":"publisher","first-page":"545","DOI":"10.1109\/TPWRS.2017.2700287","volume":"33","author":"JP Gonz\u00e1lez","year":"2018","unstructured":"Gonz\u00e1lez, J.P., San Roque, A.M., Perez, E.A.: Forecasting functional time series with a new Hilbertian ARMAX model: application to electricity price forecasting. IEEE Trans. Power Syst. 33(1), 545\u2013556 (2018)","journal-title":"IEEE Trans. Power Syst."},{"key":"108_CR28","doi-asserted-by":"publisher","first-page":"89","DOI":"10.1016\/j.ijforecast.2017.08.004","volume":"34","author":"J Luo","year":"2018","unstructured":"Luo, J., Hong, T., Fang, S.-C.: Benchmarking robustness of load forecasting models under data integrity attacks. Int. J. Forecast. 34, 89\u2013104 (2018)","journal-title":"Int. J. Forecast."},{"key":"108_CR29","unstructured":"Dong, G., Chen, Z.: Data driven energy management in a home microgrid based on Bayesian optimal algorithm. IEEE Trans. Ind. Inform"},{"key":"108_CR30","volume-title":"Fundamentals of Neural Networks: Architectures, Algorithms, and Applications","author":"L Fausett","year":"2006","unstructured":"Fausett, L.: Fundamentals of Neural Networks: Architectures, Algorithms, and Applications. Pearson Education, Delhi (2006)"},{"key":"108_CR31","doi-asserted-by":"publisher","first-page":"177","DOI":"10.1109\/69.134256","volume":"4","author":"S Shekhar","year":"1992","unstructured":"Shekhar, S., Amin, M.B.: Generalization by neural networks. IEEE Trans. Knowl. Data Eng. 4, 177\u2013185 (1992)","journal-title":"IEEE Trans. Knowl. Data Eng."}],"container-title":["Advances in Intelligent Systems and Computing","Web, Artificial Intelligence and Network Applications"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-15035-8_108","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,5,18]],"date-time":"2019-05-18T03:00:14Z","timestamp":1558148414000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-030-15035-8_108"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019]]},"ISBN":["9783030150341","9783030150358"],"references-count":31,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-15035-8_108","relation":{},"ISSN":["2194-5357","2194-5365"],"issn-type":[{"value":"2194-5357","type":"print"},{"value":"2194-5365","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019]]},"assertion":[{"value":"15 March 2019","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"WAINA","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Workshops of  the International Conference on Advanced Information Networking and Applications","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Matsue","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Japan","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2019","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"27 March 2019","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"29 March 2019","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"33","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"waina2019","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/voyager.ce.fit.ac.jp\/conf\/aina\/2019\/workshops.php","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}