{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,28]],"date-time":"2025-03-28T04:15:59Z","timestamp":1743135359476,"version":"3.40.3"},"publisher-location":"Cham","reference-count":25,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030223533"},{"type":"electronic","value":"9783030223540"}],"license":[{"start":{"date-parts":[[2019,6,21]],"date-time":"2019-06-21T00:00:00Z","timestamp":1561075200000},"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":[[2020]]},"DOI":"10.1007\/978-3-030-22354-0_7","type":"book-chapter","created":{"date-parts":[[2019,6,20]],"date-time":"2019-06-20T07:02:51Z","timestamp":1561014171000},"page":"73-86","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["A Comparative Analysis of Neural Networks and Enhancement of ELM for Short Term Load Forecasting"],"prefix":"10.1007","author":[{"given":"Rahim","family":"Ullah","sequence":"first","affiliation":[]},{"given":"Nadeem","family":"Javaid","sequence":"additional","affiliation":[]},{"given":"Ghulam","family":"Hafeez","sequence":"additional","affiliation":[]},{"given":"Salim","family":"Ullah","sequence":"additional","affiliation":[]},{"given":"Fahad","family":"Ahmad","sequence":"additional","affiliation":[]},{"given":"Ashraf","family":"Ullah","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2019,6,21]]},"reference":[{"key":"7_CR1","doi-asserted-by":"crossref","unstructured":"\u00d6nkal, D., Sayim, K.Z., Lawrence, M.: Wisdom of group forecasts: does role-playing play a role? Omega 40(6), 693\u2013702 (2012)","DOI":"10.1016\/j.omega.2011.01.010"},{"key":"7_CR2","doi-asserted-by":"publisher","first-page":"29","DOI":"10.1016\/j.knosys.2015.02.017","volume":"82","author":"I Koprinska","year":"2015","unstructured":"Koprinska, I., Rana, M., Agelidis, V.G.: Correlation and instance based feature selection for electricity load forecasting. Knowl.-Based Syst. 82, 29\u201340 (2015)","journal-title":"Knowl.-Based Syst."},{"key":"7_CR3","unstructured":"Chan, S.-C., Tsui, K.M., Wu, H.C., Hou, Y., Wu, Y.-C., Wu, F.F.: Load\/price forecasting and managing demand response for smart grids: methodologies and challenges. IEEE Sig. Process. Mag. 29(5), 68\u201385 (2012)"},{"issue":"1","key":"7_CR4","doi-asserted-by":"publisher","first-page":"657","DOI":"10.1016\/j.energy.2011.10.034","volume":"37","author":"J Che","year":"2012","unstructured":"Che, J., Wang, J., Wang, G.: An adaptive fuzzy combination model based on self-organizing map and support vector regression for electric load forecasting. Energy 37(1), 657\u2013664 (2012)","journal-title":"Energy"},{"issue":"1","key":"7_CR5","doi-asserted-by":"publisher","first-page":"23","DOI":"10.1080\/00207720110067421","volume":"33","author":"HK Alfares","year":"2002","unstructured":"Alfares, H.K., Nazeeruddin, M.: Electric load forecasting: literature survey and classification of methods. Int. J. Syst. Sci. 33(1), 23\u201334 (2002)","journal-title":"Int. J. Syst. Sci."},{"issue":"4","key":"7_CR6","doi-asserted-by":"publisher","first-page":"645","DOI":"10.1016\/j.ijforecast.2008.07.007","volume":"24","author":"JW Taylor","year":"2008","unstructured":"Taylor, J.W.: An evaluation of methods for very short-term load forecasting using minute-by-minute British data. Int. J. Forecast. 24(4), 645\u2013658 (2008)","journal-title":"Int. J. Forecast."},{"key":"7_CR7","doi-asserted-by":"publisher","first-page":"40","DOI":"10.1016\/j.apenergy.2016.05.083","volume":"177","author":"A Ghasemi","year":"2016","unstructured":"Ghasemi, A., Shayeghi, H., Moradzadeh, M., Nooshyar, M.: A novel hybrid algorithm for electricity price and load forecasting in smart grids with demand-side management. Appl. Energy 177, 40\u201359 (2016)","journal-title":"Appl. Energy"},{"key":"7_CR8","doi-asserted-by":"crossref","unstructured":"Xiao, L., Wang, J., Hou, R., Wu, J.: A combined model based on data pre-analysis and weight coefficients optimization for electrical load forecasting. Energy 82, 524\u2013549 (2015)","DOI":"10.1016\/j.energy.2015.01.063"},{"key":"7_CR9","unstructured":"Zheng, J., Xu, C., Zhang, Z., Li, X.: Electric load forecasting in smart grids using long-short-term-memory based recurrent neural network. In: 2017 51st Annual Conference on Information Sciences and Systems (CISS), pp. 1\u20136. IEEE (2017)"},{"key":"7_CR10","doi-asserted-by":"crossref","unstructured":"Park, K., Yoon, S., Hwang, E.: Hybrid load forecasting for mixed-use complex based on the characteristic load decomposition by pilot signals. IEEE Access 7, 12297\u201312306 (2019)","DOI":"10.1109\/ACCESS.2019.2892475"},{"key":"7_CR11","doi-asserted-by":"publisher","first-page":"40","DOI":"10.1016\/j.energy.2015.12.142","volume":"98","author":"J Nowotarski","year":"2016","unstructured":"Nowotarski, J., Liu, B., Weron, R., Hong, T.: Improving short term load forecast accuracy via combining sister forecasts. Energy 98, 40\u201349 (2016)","journal-title":"Energy"},{"key":"7_CR12","doi-asserted-by":"publisher","first-page":"774","DOI":"10.1016\/j.energy.2018.06.012","volume":"158","author":"J Zhang","year":"2018","unstructured":"Zhang, J., Wei, Y.-M., Li, D., Tan, Z., Zhou, J.: Short term electricity load forecasting using a hybrid model. Energy 158, 774\u2013781 (2018)","journal-title":"Energy"},{"key":"7_CR13","doi-asserted-by":"publisher","first-page":"24","DOI":"10.1016\/j.neucom.2016.09.027","volume":"221","author":"R Hu","year":"2017","unstructured":"Hu, R., Wen, S., Zeng, Z., Huang, T.: A short-term power load forecasting model based on the generalized regression neural network with decreasing step fruit fly optimization algorithm. Neurocomputing 221, 24\u201331 (2017)","journal-title":"Neurocomputing"},{"issue":"4","key":"7_CR14","doi-asserted-by":"publisher","first-page":"1535","DOI":"10.1109\/59.99410","volume":"5","author":"AD Papalexopoulos","year":"1990","unstructured":"Papalexopoulos, A.D., Hesterberg, T.C.: A regression-based approach to short-term system load forecasting. IEEE Trans. Power Syst. 5(4), 1535\u20131547 (1990)","journal-title":"IEEE Trans. Power Syst."},{"issue":"1","key":"7_CR15","doi-asserted-by":"publisher","first-page":"343","DOI":"10.1109\/59.221222","volume":"8","author":"GAN Mbamalu","year":"1993","unstructured":"Mbamalu, G.A.N., El-Hawary, M.E.: Load forecasting via suboptimal seasonal autoregressive models and iteratively reweighted least squares estimation. IEEE Trans. Power Syst. 8(1), 343\u2013348 (1993)","journal-title":"IEEE Trans. Power Syst."},{"issue":"3","key":"7_CR16","doi-asserted-by":"publisher","first-page":"187","DOI":"10.1016\/0378-7796(95)00977-1","volume":"34","author":"J-F Chen","year":"1995","unstructured":"Chen, J.-F., Wang, W.-M., Huang, C.-M.: Analysis of an adaptive time-series autoregressive moving-average (ARMA) model for short-term load forecasting. Electric Power Syst. Res. 34(3), 187\u2013196 (1995)","journal-title":"Electric Power Syst. Res."},{"issue":"2","key":"7_CR17","doi-asserted-by":"publisher","first-page":"392","DOI":"10.1109\/59.192889","volume":"3","author":"S Rahman","year":"1988","unstructured":"Rahman, S., Bhatnagar, R.: An expert system based algorithm for short term load forecast. IEEE Trans. Power Syst. 3(2), 392\u2013399 (1988)","journal-title":"IEEE Trans. Power Syst."},{"issue":"3","key":"7_CR18","doi-asserted-by":"publisher","first-page":"417","DOI":"10.1016\/j.epsr.2005.01.006","volume":"74","author":"P-F Pai","year":"2005","unstructured":"Pai, P.-F., Hong, W.-C.: Forecasting regional electricity load based on recurrent support vector machines with genetic algorithms. Electric Power Syst. Res. 74(3), 417\u2013425 (2005)","journal-title":"Electric Power Syst. Res."},{"key":"7_CR19","doi-asserted-by":"crossref","unstructured":"Pandian, S.C., Duraiswamy, K., Rajan, C.C.A., Kanagaraj, N.: Fuzzy approach for short term load forecasting. Electric Power Syst. Res. 76(6\u20137), 541\u2013548 (2006)","DOI":"10.1016\/j.epsr.2005.09.018"},{"issue":"6","key":"7_CR20","doi-asserted-by":"publisher","first-page":"6612","DOI":"10.1109\/TSG.2017.2717282","volume":"9","author":"H Chitsaz","year":"2018","unstructured":"Chitsaz, H., Zamani-Dehkordi, P., Zareipour, H., Parikh, P.P.: Electricity price forecasting for operational scheduling of behind-the-meter storage systems. IEEE Trans. Smart Grid 9(6), 6612\u20136622 (2018)","journal-title":"IEEE Trans. Smart Grid"},{"key":"7_CR21","unstructured":"NYISO: NYISO Electricity Market Data. \n                    http:\/\/www.nyiso.com\/\n                    \n                  . Accessed 8 May 2019"},{"key":"7_CR22","first-page":"280","volume":"28","author":"M Hayati","year":"2007","unstructured":"Hayati, M., Shirvany, Y.: Artificial neural network approach for short term load forecasting for Illam region. World Acad. Sci. Eng. Technol. 28, 280\u2013284 (2007)","journal-title":"World Acad. Sci. Eng. Technol."},{"key":"7_CR23","unstructured":"Dong, X., Qian, L., Huang, L.: Short-term load forecasting in smart grid: a combined CNN and K-means clustering approach. In: 2017 IEEE International Conference on Big Data and Smart Computing (BigComp), pp. 119\u2013125. IEEE (2017)"},{"issue":"3","key":"7_CR24","doi-asserted-by":"publisher","first-page":"545","DOI":"10.1109\/59.932293","volume":"16","author":"H Mori","year":"2001","unstructured":"Mori, H., Yuihara, A.: Deterministic annealing clustering for ANN-based short-term load forecasting. IEEE Trans. Power Syst. 16(3), 545\u2013551 (2001)","journal-title":"IEEE Trans. Power Syst."},{"key":"7_CR25","first-page":"985","volume":"2","author":"G-B Huang","year":"2004","unstructured":"Huang, G.-B., Zhu, Q.-Y., Siew, C.-K.: Extreme learning machine: a new learning scheme of feedforward neural networks. Neural Netw. 2, 985\u2013990 (2004)","journal-title":"Neural Netw."}],"container-title":["Advances in Intelligent Systems and Computing","Complex, Intelligent, and Software Intensive Systems"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-22354-0_7","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,6,28]],"date-time":"2019-06-28T21:34:22Z","timestamp":1561757662000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-030-22354-0_7"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,6,21]]},"ISBN":["9783030223533","9783030223540"],"references-count":25,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-22354-0_7","relation":{},"ISSN":["2194-5357","2194-5365"],"issn-type":[{"type":"print","value":"2194-5357"},{"type":"electronic","value":"2194-5365"}],"subject":[],"published":{"date-parts":[[2019,6,21]]},"assertion":[{"value":"21 June 2019","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"CISIS","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Conference on Complex, Intelligent, and Software Intensive Systems","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Sydney, NSW","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Australia","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":"3 July 2019","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"5 July 2019","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"coisis2019","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}