{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,26]],"date-time":"2025-03-26T07:07:17Z","timestamp":1742972837199,"version":"3.40.3"},"publisher-location":"Cham","reference-count":16,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783319920061"},{"type":"electronic","value":"9783319920078"}],"license":[{"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.springer.com\/tdm"},{"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.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2018]]},"DOI":"10.1007\/978-3-319-92007-8_21","type":"book-chapter","created":{"date-parts":[[2018,5,21]],"date-time":"2018-05-21T15:02:40Z","timestamp":1526914960000},"page":"240-248","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Wind Energy Forecasting at Different Time Horizons with Individual and Global Models"],"prefix":"10.1007","author":[{"given":"R.","family":"Mart\u00edn-V\u00e1zquez","sequence":"first","affiliation":[]},{"given":"R.","family":"Aler","sequence":"additional","affiliation":[]},{"given":"I. M.","family":"Galv\u00e1n","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2018,5,22]]},"reference":[{"issue":"Suppl. C","key":"21_CR1","doi-asserted-by":"publisher","first-page":"243","DOI":"10.1016\/j.rser.2014.03.033","volume":"34","author":"A Tascikaraoglu","year":"2014","unstructured":"Tascikaraoglu, A., Uzunoglu, M.: A review of combined approaches for prediction of short-term wind speed and power. Renew. Sustain. Energy Rev. 34(Suppl. C), 243\u2013254 (2014)","journal-title":"Renew. Sustain. Energy Rev."},{"key":"21_CR2","doi-asserted-by":"publisher","first-page":"762","DOI":"10.1016\/j.rser.2013.12.054","volume":"31","author":"J Jung","year":"2014","unstructured":"Jung, J., Broadwater, R.P.: Current status and future advances for wind speed and power forecasting. Renew. Sustain. Energy Rev. 31, 762\u2013777 (2014)","journal-title":"Renew. Sustain. Energy Rev."},{"issue":"4","key":"21_CR3","doi-asserted-by":"publisher","first-page":"585","DOI":"10.1016\/S0960-1481(02)00054-X","volume":"28","author":"MS Roulston","year":"2003","unstructured":"Roulston, M.S., Kaplan, D.T., Hardenberg, J., Smith, L.A.: Using medium-range weather forcasts to improve the value of wind energy production. Renew. Energy 28(4), 585\u2013602 (2003)","journal-title":"Renew. Energy"},{"key":"21_CR4","doi-asserted-by":"publisher","first-page":"201","DOI":"10.1016\/j.jweia.2014.11.014","volume":"136","author":"C Croonenbroeck","year":"2015","unstructured":"Croonenbroeck, C., Ambach, D.: A selection of time series models for short- to medium-term wind power forecasting. J. Wind Eng. Ind. Aerodyn. 136, 201\u2013210 (2015)","journal-title":"J. Wind Eng. Ind. Aerodyn."},{"key":"21_CR5","doi-asserted-by":"publisher","first-page":"724","DOI":"10.1016\/j.apenergy.2010.09.028","volume":"88","author":"H Liu","year":"2011","unstructured":"Liu, H., Erdem, E., Shi, J.: Comprehensive evaluation of ARMA-GARCH(-M) approaches for modeling the mean and volatility of wind speed. Appl. Energy 88, 724\u2013732 (2011)","journal-title":"Appl. Energy"},{"issue":"5","key":"21_CR6","doi-asserted-by":"publisher","first-page":"1388","DOI":"10.1016\/j.renene.2008.09.006","volume":"34","author":"RG Kavasseri","year":"2009","unstructured":"Kavasseri, R.G., Seetharaman, K.: Day-ahead wind speed forecasting using f-ARIMA models. Renew. Energy 34(5), 1388\u20131393 (2009)","journal-title":"Renew. Energy"},{"issue":"12","key":"21_CR7","doi-asserted-by":"publisher","first-page":"4870","DOI":"10.1016\/j.energy.2010.09.001","volume":"35","author":"H Liu","year":"2010","unstructured":"Liu, H., Shi, J., Erdem, E.: Prediction of wind speed time series using modified Taylor Kriging method. Energy 35(12), 4870\u20134879 (2010)","journal-title":"Energy"},{"key":"21_CR8","doi-asserted-by":"publisher","first-page":"122","DOI":"10.1016\/j.proenv.2012.01.256","volume":"12","author":"B Zhu","year":"2012","unstructured":"Zhu, B., Chen, M., Wade, N., Ran, L.: A prediction model for wind farm power generation based on fuzzy modeling. Procedia Environ. Sci. 12, 122\u2013129 (2012)","journal-title":"Procedia Environ. Sci."},{"issue":"2","key":"21_CR9","doi-asserted-by":"publisher","first-page":"352","DOI":"10.1109\/TEC.2003.821865","volume":"19","author":"IG Damousis","year":"2004","unstructured":"Damousis, I.G., Alexiadis, M.C., Theocharis, J.B., Dokopoulos, P.S.: A fuzzy model for wind speed prediction and power generation in wind parks using spatial correlation. IEEE Trans. Energy Convers. 19(2), 352\u2013361 (2004)","journal-title":"IEEE Trans. Energy Convers."},{"issue":"6","key":"21_CR10","doi-asserted-by":"publisher","first-page":"939","DOI":"10.1016\/j.renene.2003.11.009","volume":"29","author":"MA Mohandes","year":"2004","unstructured":"Mohandes, M.A., Halawani, T.O., Rehman, S., Hussain, A.A.: Support vector machines for wind speed prediction. Renew. Energy 29(6), 939\u2013947 (2004)","journal-title":"Renew. Energy"},{"key":"21_CR11","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"797","DOI":"10.1007\/978-3-319-11179-7_100","volume-title":"Artificial Neural Networks and Machine Learning \u2013 ICANN 2014","author":"J Heinermann","year":"2014","unstructured":"Heinermann, J., Kramer, O.: Precise wind power prediction with SVM ensemble regression. In: Wermter, S., Weber, C., Duch, W., Honkela, T., Koprinkova-Hristova, P., Magg, S., Palm, G., Villa, Alessandro E.P. (eds.) ICANN 2014. LNCS, vol. 8681, pp. 797\u2013804. Springer, Cham (2014). https:\/\/doi.org\/10.1007\/978-3-319-11179-7_100"},{"key":"21_CR12","doi-asserted-by":"publisher","first-page":"82","DOI":"10.1016\/j.rser.2015.04.081","volume":"50","author":"Y Ren","year":"2015","unstructured":"Ren, Y., Suganthan, P.N., Srikanth, N.: Ensemble methods for wind and solar power forecasting\u2014a state-of-the-art review. Renew. Sustain. Energy Rev. 50, 82\u201391 (2015)","journal-title":"Renew. Sustain. Energy Rev."},{"issue":"1","key":"21_CR13","doi-asserted-by":"publisher","first-page":"126","DOI":"10.1007\/s40565-015-0171-6","volume":"5","author":"Y Jiang","year":"2017","unstructured":"Jiang, Y., Chen, X., Yu, K., Liao, Y.: Short-term wind power forecasting using hybrid method based on enhanced boosting algorithm. J. Mod. Power Syst. Clean Energy 5(1), 126\u2013133 (2017)","journal-title":"J. Mod. Power Syst. Clean Energy"},{"key":"21_CR14","doi-asserted-by":"publisher","first-page":"202","DOI":"10.1016\/j.renene.2016.02.003","volume":"92","author":"B Doucoure","year":"2016","unstructured":"Doucoure, B., Agbossou, K., Cardenas, A.: Time series prediction using artificial wavelet neural network and multi-resolution analysis: application to wind speed data. Renew. Energy 92, 202\u2013211 (2016)","journal-title":"Renew. Energy"},{"issue":"2","key":"21_CR15","doi-asserted-by":"publisher","first-page":"656","DOI":"10.1109\/TPWRS.2013.2282366","volume":"29","author":"N Chen","year":"2014","unstructured":"Chen, N., Qian, Z., Nabney, I.T., Meng, X.: Wind power forecasts using Gaussian processes and numerical weather prediction. IEEE Trans. Power Syst. 29(2), 656\u2013665 (2014)","journal-title":"IEEE Trans. Power Syst."},{"key":"21_CR16","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"698","DOI":"10.1007\/978-3-319-59153-7_60","volume-title":"Advances in Computational Intelligence","author":"R Mart\u00edn-V\u00e1zquez","year":"2017","unstructured":"Mart\u00edn-V\u00e1zquez, R., Aler, R., Galv\u00e1n, In\u00e9s\u00a0M.: A study on feature selection methods for wind energy prediction. In: Rojas, I., Joya, G., Catala, A. (eds.) IWANN 2017. LNCS, vol. 10305, pp. 698\u2013707. Springer, Cham (2017). https:\/\/doi.org\/10.1007\/978-3-319-59153-7_60"}],"container-title":["IFIP Advances in Information and Communication Technology","Artificial Intelligence Applications and Innovations"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-319-92007-8_21","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,5,21]],"date-time":"2022-05-21T00:11:13Z","timestamp":1653091873000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-319-92007-8_21"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018]]},"ISBN":["9783319920061","9783319920078"],"references-count":16,"URL":"https:\/\/doi.org\/10.1007\/978-3-319-92007-8_21","relation":{},"ISSN":["1868-4238","1868-422X"],"issn-type":[{"type":"print","value":"1868-4238"},{"type":"electronic","value":"1868-422X"}],"subject":[],"published":{"date-parts":[[2018]]},"assertion":[{"value":"22 May 2018","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"AIAI","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"IFIP International Conference on Artificial Intelligence Applications and Innovations","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Rhodes","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Greece","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2018","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"25 May 2018","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"27 May 2018","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":"aiai2018","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/easyconferences.eu\/aiai2018\/index.html","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"This content has been made available to all.","name":"free","label":"Free to read"}]}}