{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,9,9]],"date-time":"2024-09-09T10:54:41Z","timestamp":1725879281875},"publisher-location":"Singapore","reference-count":21,"publisher":"Springer Singapore","isbn-type":[{"type":"print","value":"9789811037276"},{"type":"electronic","value":"9789811037283"}],"license":[{"start":{"date-parts":[[2017,1,1]],"date-time":"2017-01-01T00:00:00Z","timestamp":1483228800000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2017]]},"DOI":"10.1007\/978-981-10-3728-3_10","type":"book-chapter","created":{"date-parts":[[2017,1,27]],"date-time":"2017-01-27T23:42:46Z","timestamp":1485560566000},"page":"91-100","source":"Crossref","is-referenced-by-count":9,"title":["Joint Feature Selection and Parameter Tuning for Short-Term Traffic Flow Forecasting Based on Heuristically Optimized Multi-layer Neural Networks"],"prefix":"10.1007","author":[{"given":"Ibai","family":"La\u00f1a","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Javier","family":"Del Ser","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Manuel","family":"V\u00e9lez","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Izaskun","family":"Oregi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2017,1,29]]},"reference":[{"unstructured":"Van Hinsbergen, C.P., Van Lint, J.W., Sanders, F.M.: Short term traffic prediction models. In: Proceedings of the 14th World Congress on Intelligent Transport Systems (ITS), Beijing, pp. 22\u201341 (2007)","key":"10_CR1"},{"key":"10_CR2","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1016\/j.trc.2014.01.005","volume":"43","author":"EI Vlahogianni","year":"2014","unstructured":"Vlahogianni, E.I., Karlaftis, M.G., Golias, J.C.: Short-term traffic forecasting: where we are and where we\u2019re going. Transp. Res. Part C: Emerg. Technol. 43, 3\u201319 (2014)","journal-title":"Transp. Res. Part C: Emerg. Technol."},{"issue":"4","key":"10_CR3","doi-asserted-by":"crossref","first-page":"455","DOI":"10.1061\/(ASCE)TE.1943-5436.0000337","volume":"138","author":"S Dunne","year":"2011","unstructured":"Dunne, S., Ghosh, B.: Regime-based short-term multivariate traffic condition forecasting algorithm. J. Transp. Eng. 138(4), 455\u2013466 (2011)","journal-title":"J. Transp. Eng."},{"key":"10_CR4","series-title":"IFIP Advances in Information and Communication Technology","doi-asserted-by":"publisher","first-page":"108","DOI":"10.1007\/978-3-319-25261-2_10","volume-title":"Artificial Intelligence in Theory and Practice IV","author":"H Yang","year":"2015","unstructured":"Yang, H., Dillon, T.S., Chen, Y.-P.P.: Evaluation of recent computational approaches in short-term traffic forecasting. In: Dillon, T. (ed.) IFIP AI 2015. IAICT, vol. 465, pp. 108\u2013116. Springer, Heidelberg (2015). doi: 10.1007\/978-3-319-25261-2_10"},{"key":"10_CR5","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"548","DOI":"10.1007\/978-3-319-23862-3_54","volume-title":"Intelligence Science and Big Data Engineering. Big Data and Machine Learning Techniques","author":"W Zhang","year":"2015","unstructured":"Zhang, W., Xiao, R., Deng, J.: Research of traffic flow forecasting based on the information fusion of BP network sequence. In: He, X., Gao, X., Zhang, Y., Zhou, Z.-H., Liu, Z.-Y., Fu, B., Hu, F., Zhang, Z. (eds.) IScIDE 2015. LNCS, vol. 9243, pp. 548\u2013558. Springer, Heidelberg (2015). doi: 10.1007\/978-3-319-23862-3_54"},{"key":"10_CR6","doi-asserted-by":"crossref","first-page":"779","DOI":"10.1007\/s11771-015-2582-y","volume":"22","author":"M Meng","year":"2015","unstructured":"Meng, M., Shao, C.F., Wong, Y.D., Wang, B.B., Li, H.X.: A two-stage short-term traffic flow prediction method based on AVL and AKNN techniques. J. Cent. South Univ. 22, 779\u2013786 (2015)","journal-title":"J. Cent. South Univ."},{"issue":"2","key":"10_CR7","doi-asserted-by":"crossref","first-page":"e0147263","DOI":"10.1371\/journal.pone.0147263","volume":"11","author":"J Tang","year":"2016","unstructured":"Tang, J., Zou, Y., Ash, J., Zhang, S., Liu, F., Wang, Y.: Travel time estimation using freeway point detector data based on evolving fuzzy neural inference system. PloS one 11(2), e0147263 (2016)","journal-title":"PloS one"},{"key":"10_CR8","first-page":"98","volume":"1453","author":"BL Smith","year":"1994","unstructured":"Smith, B.L., Demetsky, M.J.: Short-term traffic flow prediction: neural network approach. Transp. Res. Record 1453, 98\u2013101 (1994)","journal-title":"Transp. Res. Record"},{"unstructured":"Abdulhai, B., Porwal, H., Recker, W.: Short term freeway traffic flow prediction using genetically-optimized time-delay-based neural networks. California Partners for Advanced Transit and Highways (PATH) (1999)","key":"10_CR9"},{"issue":"3","key":"10_CR10","doi-asserted-by":"crossref","first-page":"211","DOI":"10.1016\/j.trc.2005.04.007","volume":"13","author":"EI Vlahogianni","year":"2005","unstructured":"Vlahogianni, E.I., Karlaftis, M.G., Golias, J.C.: Optimized and meta-optimized neural networks for short-term traffic flow prediction: a genetic approach. Transp. Res. Part C: Emerg. Technol. 13(3), 211\u2013234 (2005)","journal-title":"Transp. Res. Part C: Emerg. Technol."},{"key":"10_CR11","doi-asserted-by":"crossref","first-page":"45","DOI":"10.3141\/1836-07","volume":"1836","author":"S Ishak","year":"2003","unstructured":"Ishak, S., Kotha, P., Alecsandru, C.: Optimization of dynamic neural network performance for short-term traffic prediction. Transp. Res. Record J. Transp. Res. Board 1836, 45\u201356 (2003)","journal-title":"Transp. Res. Record J. Transp. Res. Board"},{"issue":"3","key":"10_CR12","doi-asserted-by":"crossref","first-page":"213","DOI":"10.1080\/03081060500120340","volume":"28","author":"M Zhong","year":"2005","unstructured":"Zhong, M., Sharma, S., Lingras, P.: Refining genetically designed models for improved traffic prediction on rural roads. Transp. Plan. Technol. 28(3), 213\u2013236 (2005)","journal-title":"Transp. Plan. Technol."},{"issue":"2","key":"10_CR13","first-page":"50","volume":"1","author":"A Nagare","year":"2012","unstructured":"Nagare, A., Bhatia, S.: Traffic flow control using neural network. Traffic 1(2), 50\u201352 (2012)","journal-title":"Traffic"},{"key":"10_CR14","doi-asserted-by":"crossref","first-page":"156","DOI":"10.1007\/s12204-015-1604-0","volume":"20","author":"SY Liu","year":"2015","unstructured":"Liu, S.Y., Li, D.W., Xi, Y.G., Tang, Q.F.: A short-term traffic flow forecasting method and its applications. J. Shanghai Jiaotong Univ. 20, 156\u2013163 (2015)","journal-title":"J. Shanghai Jiaotong Univ."},{"issue":"2","key":"10_CR15","doi-asserted-by":"crossref","first-page":"60","DOI":"10.1177\/003754970107600201","volume":"76","author":"ZW Geem","year":"2001","unstructured":"Geem, Z.W., Kim, J.H., Loganathan, G.V.: A new heuristic optimization algorithm: harmony search. Simulation 76(2), 60\u201368 (2001)","journal-title":"Simulation"},{"key":"10_CR16","first-page":"1157","volume-title":"Network Operations and Management (NOMS)","author":"I La\u00f1a","year":"2016","unstructured":"La\u00f1a, I., Del Ser, J., Olabarrieta, I.: Understanding daily mobility patterns in urban road networks using traffic flow analytics. Network Operations and Management (NOMS), pp. 1157\u20131162. IEEE, Istanbul (2016)"},{"unstructured":"Madrid Open Data portal. http:\/\/datos.madrid.es . Accessed 18 Nov 2016","key":"10_CR17"},{"issue":"1","key":"10_CR18","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1162\/evco.1993.1.1.1","volume":"1","author":"T B\u00e4ck","year":"1993","unstructured":"B\u00e4ck, T., Schwefel, H.: An overview of evolutionary algorithms for parameter optimization. Evol. Comput. 1(1), 1\u201323 (1993)","journal-title":"Evol. Comput."},{"key":"10_CR19","first-page":"293","volume-title":"International Conference on Future Computer and Communication","author":"W Hu","year":"2010","unstructured":"Hu, W., Liu, Y., Li, L., Xin, S.: The short-term traffic flow prediction based on neural network. International Conference on Future Computer and Communication, pp. 293\u2013296. IEEE, Wuhan (2010)"},{"key":"10_CR20","doi-asserted-by":"crossref","first-page":"317","DOI":"10.1111\/j.1467-8667.2007.00488.x","volume":"22","author":"EI Vlahogianni","year":"2007","unstructured":"Vlahogianni, E.I., Karlaftis, M.G., Golias, J.C.: Spatio-temporal short-term urban traffic volume forecasting using genetically optimized modular networks. Comput. Aided Civil Infrastruct. Eng. 22, 317\u2013325 (2007)","journal-title":"Comput. Aided Civil Infrastruct. Eng."},{"key":"10_CR21","doi-asserted-by":"crossref","first-page":"31","DOI":"10.1109\/2.485891","volume":"29","author":"AK Jain","year":"1996","unstructured":"Jain, A.K., Mao, J., Mohiuddin, K.M.: Artificial neural networks - a tutorial. Computer 29, 31\u201344 (1996)","journal-title":"Computer"}],"container-title":["Advances in Intelligent Systems and Computing","Harmony Search Algorithm"],"original-title":[],"link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-10-3728-3_10","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2017,6,25]],"date-time":"2017-06-25T05:13:51Z","timestamp":1498367631000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-981-10-3728-3_10"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017]]},"ISBN":["9789811037276","9789811037283"],"references-count":21,"URL":"https:\/\/doi.org\/10.1007\/978-981-10-3728-3_10","relation":{},"ISSN":["2194-5357","2194-5365"],"issn-type":[{"type":"print","value":"2194-5357"},{"type":"electronic","value":"2194-5365"}],"subject":[],"published":{"date-parts":[[2017]]}}}