{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,13]],"date-time":"2026-04-13T23:41:27Z","timestamp":1776123687675,"version":"3.50.1"},"publisher-location":"Cham","reference-count":32,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783030578015","type":"print"},{"value":"9783030578022","type":"electronic"}],"license":[{"start":{"date-parts":[[2020,8,29]],"date-time":"2020-08-29T00:00:00Z","timestamp":1598659200000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2020,8,29]],"date-time":"2020-08-29T00:00:00Z","timestamp":1598659200000},"content-version":"vor","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":[[2021]]},"DOI":"10.1007\/978-3-030-57802-2_55","type":"book-chapter","created":{"date-parts":[[2020,8,28]],"date-time":"2020-08-28T07:05:27Z","timestamp":1598598327000},"page":"571-579","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["A Comparison of Multivariate Time Series Clustering Methods"],"prefix":"10.1007","author":[{"given":"Iago","family":"V\u00e1zquez","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jos\u00e9 Ram\u00f3n","family":"Villar","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Javier","family":"Sedano","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Svetlana","family":"Simi\u0107","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2020,8,29]]},"reference":[{"key":"55_CR1","doi-asserted-by":"publisher","first-page":"401","DOI":"10.1016\/j.solener.2019.01.041","volume":"180","author":"G Liu","year":"2019","unstructured":"Liu, G., Zhu, L., Wu, X., Wang, J.: Time series clustering and physical implication for photovoltaic array systems with unknown working conditions. Sol. Energy 180, 401\u2013411 (2019)","journal-title":"Sol. Energy"},{"key":"55_CR2","doi-asserted-by":"publisher","first-page":"236","DOI":"10.1016\/j.compchemeng.2018.08.026","volume":"118","author":"Y Lee","year":"2018","unstructured":"Lee, Y., Na, J., Lee, W.B.: Robust design of ambient-air vaporizer based on time-series clustering. Comput. Chem. Eng. 118, 236\u2013247 (2018)","journal-title":"Comput. Chem. Eng."},{"key":"55_CR3","doi-asserted-by":"publisher","first-page":"16","DOI":"10.1016\/j.is.2015.04.007","volume":"53","author":"S Aghabozorgi","year":"2015","unstructured":"Aghabozorgi, S., Shirkhorshidi, A.S., Wah, T.Y.: Time-series clustering - a decade review. Inf. Syst. 53, 16\u201338 (2015)","journal-title":"Inf. Syst."},{"key":"55_CR4","doi-asserted-by":"publisher","first-page":"12","DOI":"10.1016\/j.ijar.2018.05.002","volume":"99","author":"P D\u2019Urso","year":"2018","unstructured":"D\u2019Urso, P., Giovanni, L.D., Massari, R.: Robust fuzzy clustering of multivariate time trajectories. Int. J. Approximate Reasoning 99, 12\u201338 (2018)","journal-title":"Int. J. Approximate Reasoning"},{"key":"55_CR5","doi-asserted-by":"publisher","first-page":"513","DOI":"10.1016\/j.isatra.2017.09.004","volume":"71","author":"CH Fontes","year":"2017","unstructured":"Fontes, C.H., Budman, H.: A hybrid clustering approach for multivariate time series - a case study applied to failure analysis in a gas turbine. ISA Trans. 71, 513\u2013529 (2017)","journal-title":"ISA Trans."},{"key":"55_CR6","doi-asserted-by":"publisher","first-page":"220","DOI":"10.1016\/j.ins.2018.10.047","volume":"477","author":"M Hu","year":"2019","unstructured":"Hu, M., Feng, X., Ji, Z., Yan, K., Zhou, S.: A novel computational approach for discord search with local recurrence rates in multivariate time series. Inf. Sci. 477, 220\u2013233 (2019)","journal-title":"Inf. Sci."},{"key":"55_CR7","doi-asserted-by":"publisher","first-page":"337","DOI":"10.1016\/j.ins.2018.10.026","volume":"476","author":"C Yu","year":"2019","unstructured":"Yu, C., Luo, L., Chan, L.L.H., Rakthanmanon, T., Nutanong, S.: A fast LSH-based similarity search method for multivariate time series. Inf. Sci. 476, 337\u2013356 (2019)","journal-title":"Inf. Sci."},{"key":"55_CR8","doi-asserted-by":"publisher","first-page":"569","DOI":"10.1016\/j.patcog.2017.11.030","volume":"76","author":"K\u00d8 Mikalsen","year":"2018","unstructured":"Mikalsen, K.\u00d8., Bianchi, F.M., Soguero-Ruiz, C., Jenssen, R.: Time series cluster kernel for learning similarities between multivariate time series with missing data. Pattern Recogn. 76, 569\u2013581 (2018)","journal-title":"Pattern Recogn."},{"key":"55_CR9","doi-asserted-by":"crossref","unstructured":"V\u00e1zquez, I., Villar, J.R., Sedano, J., Simic, S.: A preliminary study on multivariate time series clustering. In: 14th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2019) - Seville, Spain, 13\u201315 May 2019, Proceedings, pp. 473\u2013480 (2019)","DOI":"10.1007\/978-3-030-20055-8_45"},{"key":"55_CR10","doi-asserted-by":"crossref","unstructured":"V\u00e1zquez, I., Villar, J.R., Sedano, J., Simic, S., de la Cal, E.A.: A proof of concept in multivariate time series clustering using recurrent neural networks and SP-lines. In: Hybrid Artificial Intelligent Systems - 14th International Conference, HAIS 2019, Le\u00f3n, Spain, 4\u20136 September 2019, Proceedings, pp. 346\u2013357 (2019)","DOI":"10.1007\/978-3-030-29859-3_30"},{"key":"55_CR11","doi-asserted-by":"crossref","unstructured":"Ferreira, A.M.S., de Oliveira Fontes, C.H., Cavalcante, C.A.M.T., Marambio, J.E.S.: Pattern recognition as a tool to support decision making in the management of the electric sector. Part II: a new method based on clustering of multivariate time series. Int. J. Electr. Power Energy Syst. 67, 613\u2013626 (2015)","DOI":"10.1016\/j.ijepes.2014.12.001"},{"key":"55_CR12","unstructured":"Salvo, R.D., Montalto, P., Nunnari, G., Neri, M., Puglisi, G.: Multivariate time series clustering on geophysical data recorded at Mt. Etna from 1996 to 2003. J. Volcanol. Geoth. Res. 251, 65\u201374 (2013). Flank instability at Mt. Etna"},{"key":"55_CR13","doi-asserted-by":"publisher","first-page":"229","DOI":"10.1016\/j.asoc.2017.06.035","volume":"60","author":"J Li","year":"2017","unstructured":"Li, J., Pedrycz, W., Jamal, I.: Multivariate time series anomaly detection: a framework of hidden Markov models. Appl. Soft Comput. 60, 229\u2013240 (2017)","journal-title":"Appl. Soft Comput."},{"key":"55_CR14","doi-asserted-by":"publisher","first-page":"1053","DOI":"10.1016\/j.asoc.2018.09.032","volume":"73","author":"L Duan","year":"2018","unstructured":"Duan, L., Yu, F., Pedrycz, W., Wang, X., Yang, X.: Time-series clustering based on linear fuzzy information granules. Appl. Soft Comput. 73, 1053\u20131067 (2018)","journal-title":"Appl. Soft Comput."},{"key":"55_CR15","doi-asserted-by":"publisher","first-page":"1337","DOI":"10.1016\/j.apenergy.2019.01.196","volume":"238","author":"G Bode","year":"2019","unstructured":"Bode, G., Schreiber, T., Baranski, M., M\u00fcller, D.: A time series clustering approach for building automation and control systems. Appl. Energy 238, 1337\u20131345 (2019)","journal-title":"Appl. Energy"},{"key":"55_CR16","unstructured":"Anstey, J., Peters, D., Dawson, C.: An improved feature extraction technique for high volume time series data. In: Proceedings of the Fourth IASTED International Conference on Signal Processing, Pattern Recognition, and Applications, pp. 74\u201381, January 2007"},{"key":"55_CR17","doi-asserted-by":"crossref","unstructured":"Keogh, E., Lonardi, S., Chiu, B.Y.c.: Finding surprising patterns in a time series database in linear time and space. In: Proceedings of the Eighth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 550\u2013556 (2002)","DOI":"10.1145\/775047.775128"},{"key":"55_CR18","doi-asserted-by":"publisher","first-page":"188","DOI":"10.1145\/568518.568520","volume":"27","author":"K Chakrabarti","year":"2002","unstructured":"Chakrabarti, K., Keogh, E., Mehrotra, S., Pazzani, M.: Locally adaptive dimensionality reduction for indexing large time series databases. ACM Trans. Database Syst. (TODS) 27, 188\u2013228 (2002)","journal-title":"ACM Trans. Database Syst. (TODS)"},{"key":"55_CR19","unstructured":"Chan, K.P., Fu, A.W.C.: Efficient time series matching by wavelets. In: Proceedings of the 15th International Conference on Data Engineering, p. 126 (1999)"},{"key":"55_CR20","doi-asserted-by":"publisher","DOI":"10.1515\/9781400874668","volume-title":"Adaptive Control Processes","author":"R Bellman","year":"1961","unstructured":"Bellman, R.: Adaptive Control Processes. Princeton University Press, Princeton (1961)"},{"issue":"2","key":"55_CR21","doi-asserted-by":"publisher","first-page":"93","DOI":"10.1109\/TAU.1969.1162042","volume":"17","author":"R Singleton","year":"1969","unstructured":"Singleton, R.: An algorithm for computing the mixed radix fast Fourier transform. IEEE Trans. Audio Electroacoust. 17(2), 93\u2013103 (1969)","journal-title":"IEEE Trans. Audio Electroacoust."},{"key":"55_CR22","doi-asserted-by":"publisher","first-page":"99","DOI":"10.1007\/s10618-006-0049-3","volume":"14","author":"E Keogh","year":"2007","unstructured":"Keogh, E., Lonardi, S., Ratanamahatana, C., Wei, L., Lee, S.H., Handley, J.: Compression-based data mining of sequential data. Data Min. Knowl. Disc. 14, 99\u2013129 (2007)","journal-title":"Data Min. Knowl. Disc."},{"key":"55_CR23","doi-asserted-by":"crossref","unstructured":"\u00d6zt\u00fcrk, A., Lallich, S., Darmont, J.: A visual quality index for fuzzy C-means. In: Artificial Intelligence Applications and Innovations, June 2018","DOI":"10.1007\/978-3-319-92007-8_46"},{"issue":"3","key":"55_CR24","doi-asserted-by":"publisher","first-page":"606","DOI":"10.1007\/s10618-016-0483-9","volume":"31","author":"A Bagnall","year":"2017","unstructured":"Bagnall, A., Lines, J., Bostrom, A., Large, J., Keogh, E.: The great time series classification bake off: a review and experimental evaluation of recent algorithmic advances. Data Min. Knowl. Disc. 31(3), 606\u2013660 (2017)","journal-title":"Data Min. Knowl. Disc."},{"key":"55_CR25","unstructured":"Wang, J., Balasubramanian, A., de la Vega, L.M., Green, J.R., Samal, A., Prabhakaran, B.: Word recognition from continuous articulatory movement time-series data using symbolic representations. In: ACL\/ISCA Interspeech Workshop on Speech and Language Processing for Assistive Technologies, pp. 119\u2013127 (2013)"},{"issue":"1","key":"55_CR26","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s10618-016-0455-0","volume":"31","author":"M Shokoohi-Yekta","year":"2017","unstructured":"Shokoohi-Yekta, M., HuHongxia, B., Wang, J., Keogh, E.: Generalizing DTW to the multi-dimensional case requires an adaptive approach. Data Min. Knowl. Disc. 31(1), 1\u201331 (2017)","journal-title":"Data Min. Knowl. Disc."},{"key":"55_CR27","unstructured":"Ko, M., West, G., Venkatesh, S., Kumar, M.: Online context recognition in multisensor systems using dynamic time warping. In: Proceedings of the IEEE International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP), pp. 283\u2013288 (2005)"},{"issue":"06","key":"55_CR28","doi-asserted-by":"publisher","first-page":"1650037","DOI":"10.1142\/S0129065716500374","volume":"26","author":"JR Villar","year":"2016","unstructured":"Villar, J.R., Vergara, P., Men\u00e9ndez, M., de la Cal, E., Gonz\u00e1lez, V.M., Sedano, J.: Generalized models for the classification of abnormal movements in daily life and its applicability to epilepsy convulsion recognition. Int. J. Neural Syst. 26(06), 1650037 (2016)","journal-title":"Int. J. Neural Syst."},{"key":"55_CR29","unstructured":"Blankertz, B., Curio, G., Muller, K.R.: No Title. In: Advances in Neural Information Processing Systems 14 (NIPS 2001) (2011)"},{"issue":"23","key":"55_CR30","doi-asserted-by":"publisher","first-page":"E215","DOI":"10.1161\/01.CIR.101.23.e215","volume":"101","author":"AL Goldberger","year":"2000","unstructured":"Goldberger, A.L., Amaral, L.A.N., Glass, L., Hausdorff, J.M., Ivanov, P.C., Mark, R.G., Mietus, J.E., Moody, G.B., Peng, C.K., Stanley, H.E.: PhysioBank, PhysioToolkit, and PhysioNet components of a new research resource for complex physiologic signals. Circulation 101(23), E215\u2013E220 (2000)","journal-title":"Circulation"},{"issue":"12","key":"55_CR31","doi-asserted-by":"publisher","first-page":"2181","DOI":"10.1088\/0967-3334\/37\/12\/2181","volume":"37","author":"C Liu","year":"2016","unstructured":"Liu, C., Springer, D., Li, Q., Moody, B., Juan, R.A., Chorro, F.J., Castells, F., Roig, J.M., Silva, I., Johnson, A.E.W., Syed, Z., Schmidt, S.E., Papadaniil, C.D., Hadjileontiadis, L., Naseri, H., Moukadem, A., Dieterlen, A., Brandt, C., Tang, H., Samieinasab, M., Samieinasab, M.R., SameniRoger, R., Mark, G., Clifford, G.D.: An open access database for the evaluation of heart sound algorithms. Physiol. Meas. 37(12), 2181\u20132213 (2016)","journal-title":"Physiol. Meas."},{"key":"55_CR32","doi-asserted-by":"crossref","unstructured":"Zakaria, J., Mueen, A., Keogh, E.: Clustering time series using unsupervised-shapelets. In: Proceedings of the 2012 IEEE 12th International Conference on Data Mining, pp. 785\u2013794 (2012)","DOI":"10.1109\/ICDM.2012.26"}],"container-title":["Advances in Intelligent Systems and Computing","15th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2020)"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-57802-2_55","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,8,28]],"date-time":"2020-08-28T07:19:24Z","timestamp":1598599164000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-030-57802-2_55"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,8,29]]},"ISBN":["9783030578015","9783030578022"],"references-count":32,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-57802-2_55","relation":{},"ISSN":["2194-5357","2194-5365"],"issn-type":[{"value":"2194-5357","type":"print"},{"value":"2194-5365","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,8,29]]},"assertion":[{"value":"29 August 2020","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"SOCO","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Workshop on Soft Computing Models in Industrial and Environmental Applications","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Burgos","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Spain","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2020","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"16 September 2020","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"18 September 2020","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"15","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"socomoin2020","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/2020.sococonference.eu\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}