{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,10]],"date-time":"2025-12-10T08:46:09Z","timestamp":1765356369464,"version":"3.37.3"},"publisher-location":"Singapore","reference-count":22,"publisher":"Springer Singapore","isbn-type":[{"type":"print","value":"9789811302916"},{"type":"electronic","value":"9789811302923"}],"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"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2018]]},"DOI":"10.1007\/978-981-13-0292-3_8","type":"book-chapter","created":{"date-parts":[[2018,4,13]],"date-time":"2018-04-13T18:39:00Z","timestamp":1523644740000},"page":"125-143","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["SD-HOC: Seasonal Decomposition Algorithm for Mining Lagged Time Series"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0017-6586","authenticated-orcid":false,"given":"Irvan B.","family":"Arief-Ang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Flora D.","family":"Salim","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Margaret","family":"Hamilton","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2018,4,14]]},"reference":[{"key":"8_CR1","unstructured":"U.S. Department of Energy (DOE): Building Energy Databook. Technical report (2010)"},{"key":"8_CR2","doi-asserted-by":"publisher","first-page":"28","DOI":"10.1016\/j.enbuild.2015.11.071","volume":"112","author":"LM Candanedo","year":"2016","unstructured":"Candanedo, L.M., Feldheim, V.: Accurate occupancy detection of an office room from light, temperature, humidity and $${\\rm CO}_2$$CO2 measurements using statistical learning models. Energy Build. 112, 28\u201339 (2016)","journal-title":"Energy Build."},{"key":"8_CR3","unstructured":"Ekwevugbe, T., Brown, N., Pakka, V.: Realt-time building occupancy sensing for supporting demand driven hvac operations. Energy Systems Laboratory (2013)"},{"key":"8_CR4","unstructured":"Hailemariam, E., Goldstein, R., Attar, R., Khan, A.: Real-time occupancy detection using decision trees with multiple sensor types. In: Proceedings of the 2011 Symposium on Simulation for Architecture and Urban Design, pp. 141\u2013148. Society for Computer Simulation International (2011)"},{"key":"8_CR5","doi-asserted-by":"crossref","unstructured":"Khan, A., Nicholson, J., Mellor, S., Jackson, D., Ladha, K., Ladha, C., Hand, J., Clarke, J., Olivier, P., Pl\u00f6tz, T.: Occupancy monitoring using environmental & context sensors and a hierarchical analysis framework. In: BuildSys@ SenSys, pp. 90\u201399 (2014)","DOI":"10.1145\/2674061.2674080"},{"issue":"7","key":"8_CR6","doi-asserted-by":"publisher","first-page":"881","DOI":"10.1016\/j.buildenv.2004.08.026","volume":"40","author":"T Leephakpreeda","year":"2005","unstructured":"Leephakpreeda, T.: Adaptive occupancy-based lighting control via grey prediction. Build. Environ. 40(7), 881\u2013886 (2005)","journal-title":"Build. Environ."},{"key":"8_CR7","doi-asserted-by":"publisher","first-page":"264","DOI":"10.1016\/j.enbuild.2015.08.032","volume":"107","author":"D Yan","year":"2015","unstructured":"Yan, D., OBrien, W., Hong, T., Feng, X., Gunay, H.B., Tahmasebi, F., Mahdavi, A.: Occupant behavior modeling for building performance simulation: current state and future challenges. Energy Buildings 107, 264\u2013278 (2015)","journal-title":"Energy Buildings"},{"key":"8_CR8","doi-asserted-by":"crossref","unstructured":"Ang, I.B.A., Salim, F.D., Hamilton, M.: Human occupancy recognition with multivariate ambient sensors. In: 2016 IEEE International Conference on Pervasive Computing and Communication Workshops (PerCom Workshops), pp. 1\u20136. IEEE (2016)","DOI":"10.1109\/PERCOMW.2016.7457116"},{"key":"8_CR9","doi-asserted-by":"crossref","unstructured":"Basu, C., Koehler, C., Das, K., Dey, A.K.: PerCCS: person-count from carbon dioxide using sparse non-negative matrix factorization. In: Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing, pp. 987\u2013998. ACM (2015)","DOI":"10.1145\/2750858.2807525"},{"key":"8_CR10","first-page":"1452","volume":"145","author":"KP Lam","year":"2009","unstructured":"Lam, K.P., H\u00f6ynck, M., Dong, B., Andrews, B., Chiou, Y.S., Zhang, R., Benitez, D., Choi, J., et al.: Occupancy detection through an extensive environmental sensor network in an open-plan office building. IBPSA Building Simul. 145, 1452\u20131459 (2009)","journal-title":"IBPSA Building Simul."},{"key":"8_CR11","doi-asserted-by":"crossref","unstructured":"Erickson, V.L., Lin, Y., Kamthe, A., Brahme, R., Surana, A., Cerpa, A.E., Sohn, M.D., Narayanan, S.: Energy efficient building environment control strategies using real-time occupancy measurements. In: Proceedings of the First ACM Workshop on Embedded Sensing Systems for Energy-Efficiency in Buildings, pp. 19\u201324. ACM (2009)","DOI":"10.1145\/1810279.1810284"},{"issue":"2","key":"8_CR12","doi-asserted-by":"publisher","first-page":"223","DOI":"10.1016\/j.pmcj.2010.08.003","volume":"7","author":"H Lee","year":"2011","unstructured":"Lee, H., Wu, C., Aghajan, H.: Vision-based user-centric light control for smart environments. Pervasive Mob. Comput. 7(2), 223\u2013240 (2011)","journal-title":"Pervasive Mob. Comput."},{"key":"8_CR13","doi-asserted-by":"publisher","first-page":"136","DOI":"10.1016\/j.buildenv.2015.03.029","volume":"90","author":"S Dedesko","year":"2015","unstructured":"Dedesko, S., Stephens, B., Gilbert, J.A., Siegel, J.A.: Methods to assess human occupancy and occupant activity in hospital patient rooms. Build. Environ. 90, 136\u2013145 (2015)","journal-title":"Build. Environ."},{"key":"8_CR14","doi-asserted-by":"publisher","first-page":"39","DOI":"10.1016\/j.buildenv.2014.12.011","volume":"86","author":"D Cali","year":"2015","unstructured":"Cali, D., Matthes, P., Huchtemann, K., Streblow, R., M\u00fcller, D.: $${\\rm CO}_2$$CO2 based occupancy detection algorithm: experimental analysis and validation for office and residential buildings. Build. Environ. 86, 39\u201349 (2015)","journal-title":"Build. Environ."},{"issue":"7","key":"8_CR15","doi-asserted-by":"publisher","first-page":"1381","DOI":"10.1109\/JSAC.2015.2430272","volume":"33","author":"S Depatla","year":"2015","unstructured":"Depatla, S., Muralidharan, A., Mostofi, Y.: Occupancy estimation using only WIFI power measurements. IEEE J. Sel. Areas Commun. 33(7), 1381\u20131393 (2015)","journal-title":"IEEE J. Sel. Areas Commun."},{"key":"8_CR16","doi-asserted-by":"crossref","unstructured":"Arief-Ang, I.B., Salim, F.D., Hamilton, M.: DA-HOC: semi-supervised domain adaptation for room occupancy prediction using $${\\rm CO}_2$$CO2 sensor data. In: Proceedings of the 4th ACM International Conference on Systems for Energy-Efficient Built Environments (BuildSys 2017), pp. 1\u201310. ACM (2017)","DOI":"10.1145\/3137133.3137146"},{"key":"8_CR17","unstructured":"Shiskin, J., Young, A.H., Musgrave, J.C.: The X-11 variant of the census method II seasonal adjustment program. Number 15. US Department of Commerce, Bureau of the Census (1965)"},{"issue":"2","key":"8_CR18","doi-asserted-by":"crossref","first-page":"127","DOI":"10.1080\/07350015.1998.10524743","volume":"16","author":"DF Findley","year":"1998","unstructured":"Findley, D.F., Monsell, B.C., Bell, W.R., Otto, M.C., Chen, B.C.: New capabilities and methods of the X-12-ARIMA seasonal-adjustment program. J. Bus. Econ. Stat. 16(2), 127\u2013152 (1998)","journal-title":"J. Bus. Econ. Stat."},{"key":"8_CR19","first-page":"866","volume-title":"Moving Averages","author":"RJ Hyndman","year":"2011","unstructured":"Hyndman, R.J.: Moving Averages, pp. 866\u2013869. Springer, Heidelberg (2011)"},{"issue":"6","key":"8_CR20","doi-asserted-by":"publisher","first-page":"716","DOI":"10.1109\/TAC.1974.1100705","volume":"19","author":"H Akaike","year":"1974","unstructured":"Akaike, H.: A new look at the statistical model identification. IEEE Trans. Autom. Control 19(6), 716\u2013723 (1974)","journal-title":"IEEE Trans. Autom. Control"},{"issue":"3","key":"8_CR21","doi-asserted-by":"publisher","first-page":"678","DOI":"10.1016\/j.patcog.2010.09.013","volume":"44","author":"F Petitjean","year":"2011","unstructured":"Petitjean, F., Ketterlin, A., Gan\u00e7arski, P.: A global averaging method for dynamic time warping, with applications to clustering. Pattern Recogn. 44(3), 678\u2013693 (2011)","journal-title":"Pattern Recogn."},{"key":"8_CR22","doi-asserted-by":"crossref","unstructured":"Wicker, J., Krauter, N., Derstorff, B., St\u00f6nner, C., Bourtsoukidis, E., Kl\u00fcpfel, T., Williams, J., Kramer, S.: Cinema data mining: the smell of fear. In: Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 1295\u20131304. ACM (2015)","DOI":"10.1145\/2783258.2783404"}],"container-title":["Communications in Computer and Information Science","Data Mining"],"original-title":[],"link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-13-0292-3_8","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,7,6]],"date-time":"2024-07-06T00:40:53Z","timestamp":1720226453000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-981-13-0292-3_8"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018]]},"ISBN":["9789811302916","9789811302923"],"references-count":22,"URL":"https:\/\/doi.org\/10.1007\/978-981-13-0292-3_8","relation":{},"ISSN":["1865-0929","1865-0937"],"issn-type":[{"type":"print","value":"1865-0929"},{"type":"electronic","value":"1865-0937"}],"subject":[],"published":{"date-parts":[[2018]]}}}