乐胖代购免代理版

{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,9,11]],"date-time":"2024-09-11T12:31:57Z","timestamp":1726057917895},"publisher-location":"Cham","reference-count":12,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030325909"},{"type":"electronic","value":"9783030325916"}],"license":[{"start":{"date-parts":[[2019,11,7]],"date-time":"2019-11-07T00:00:00Z","timestamp":1573084800000},"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\/978-3-030-32591-6_60","type":"book-chapter","created":{"date-parts":[[2019,11,6]],"date-time":"2019-11-06T13:03:30Z","timestamp":1573045410000},"page":"557-565","update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Random Forest-Based Ensemble Estimator for Concrete Compressive Strength Prediction via AdaBoost Method"],"prefix":"10.1007","author":[{"given":"Yuanxin","family":"Lv","sequence":"first","affiliation":[]},{"given":"Xiaoyu","family":"Shi","sequence":"additional","affiliation":[]},{"given":"Longyu","family":"Ran","sequence":"additional","affiliation":[]},{"given":"Mingsheng","family":"Shang","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2019,11,7]]},"reference":[{"issue":"4","key":"60_CR1","doi-asserted-by":"publisher","first-page":"487","DOI":"10.1016\/S0008-8846(97)00039-2","volume":"27","author":"D Wang","year":"1997","unstructured":"Wang, D., Chen, Z.: On predicting compressive strengths of mortars with ternary blends of cement, GGBFS and fly ash. Cem. Concr. Res. 27(4), 487\u2013493 (1997)","journal-title":"Cem. Concr. Res."},{"issue":"5","key":"60_CR2","first-page":"593","volume":"95","author":"S Popovics","year":"1998","unstructured":"Popovics, S.: History of a mathematical model for strength development of Portland cement concrete. Mater. J. 95(5), 593\u2013600 (1998)","journal-title":"Mater. J."},{"issue":"2","key":"60_CR3","doi-asserted-by":"crossref","first-page":"115","DOI":"10.1520\/CCA10289J","volume":"16","author":"P Rougeron","year":"1994","unstructured":"Rougeron, P., A\u00eftcin, P.C.: Optimization of the composition of a high-performance concrete. Cem. Concr. Aggreg. 16(2), 115\u2013124 (1994)","journal-title":"Cem. Concr. Aggreg."},{"issue":"12","key":"60_CR4","doi-asserted-by":"publisher","first-page":"1797","DOI":"10.1016\/S0008-8846(98)00165-3","volume":"28","author":"IC Yeh","year":"1998","unstructured":"Yeh, I.C.: Modeling of strength of high-performance concrete using artificial neural networks. Cem. Concr. Res. 28(12), 1797\u20131808 (1998)","journal-title":"Cem. Concr. Res."},{"issue":"4","key":"60_CR5","doi-asserted-by":"publisher","first-page":"316","DOI":"10.1111\/mice.12422","volume":"34","author":"T Nguyen","year":"2019","unstructured":"Nguyen, T., Kashani, A., Ngo, T., et al.: Deep neural network with high-order neuron for the prediction of foamed concrete strength. Comput.-Aided Civil Infrastruct. Eng. 34(4), 316\u2013332 (2019)","journal-title":"Comput.-Aided Civil Infrastruct. Eng."},{"key":"60_CR6","doi-asserted-by":"publisher","first-page":"562","DOI":"10.1016\/j.conbuildmat.2018.04.169","volume":"175","author":"F Deng","year":"2018","unstructured":"Deng, F., He, Y., Zhou, S., et al.: Compressive strength prediction of recycled concrete based on deep learning. Constr. Build. Mater. 175, 562\u2013569 (2018)","journal-title":"Constr. Build. Mater."},{"issue":"1","key":"60_CR7","doi-asserted-by":"publisher","first-page":"5","DOI":"10.1023\/A:1010933404324","volume":"45","author":"L Breiman","year":"2001","unstructured":"Breiman, L.: Random forests. Mach. Learn. 45(1), 5\u201332 (2001)","journal-title":"Mach. Learn."},{"issue":"2","key":"60_CR8","first-page":"197","volume":"5","author":"RE Schapire","year":"1990","unstructured":"Schapire, R.E.: The strength of weak learnability. Mach. Learn. 5(2), 197\u2013227 (1990)","journal-title":"Mach. Learn."},{"key":"60_CR9","doi-asserted-by":"crossref","unstructured":"Freund, Y., Schapire, E.R.: A desicion-theoretic generalization of on-line learning and an application to boosting. Computational Learning Theory (1995)","DOI":"10.1007\/3-540-59119-2_166"},{"issue":"1","key":"60_CR10","doi-asserted-by":"publisher","first-page":"171","DOI":"10.1007\/s00521-011-0734-z","volume":"21","author":"AH Gandomi","year":"2012","unstructured":"Gandomi, A.H., Alavi, A.H.: A new multi-gene genetic programming approach to nonlinear system modeling. Part I: materials and structural engineering problems. Neural Comput. Appl. 21(1), 171\u2013187 (2012)","journal-title":"Neural Comput. Appl."},{"key":"60_CR11","doi-asserted-by":"publisher","first-page":"554","DOI":"10.1016\/j.conbuildmat.2013.08.078","volume":"49","author":"JS Chou","year":"2013","unstructured":"Chou, J.S., Pham, A.D.: Enhanced artificial intelligence for ensemble approach to predicting high performance concrete compressive strength. Constr. Build. Mater. 49, 554\u2013563 (2013)","journal-title":"Constr. Build. Mater."},{"issue":"3","key":"60_CR12","doi-asserted-by":"publisher","first-page":"242","DOI":"10.1061\/(ASCE)CP.1943-5487.0000088","volume":"25","author":"JS Chou","year":"2010","unstructured":"Chou, J.S., Chiu, C.K., Farfoura, M., et al.: Optimizing the prediction accuracy of concrete compressive strength based on a comparison of data-mining techniques. J. Comput. Civil Eng. 25(3), 242\u2013253 (2010)","journal-title":"J. Comput. Civil Eng."}],"container-title":["Advances in Intelligent Systems and Computing","Advances in Natural Computation, Fuzzy Systems and Knowledge Discovery"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-32591-6_60","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,10,3]],"date-time":"2022-10-03T20:12:33Z","timestamp":1664827953000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-030-32591-6_60"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,11,7]]},"ISBN":["9783030325909","9783030325916"],"references-count":12,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-32591-6_60","relation":{},"ISSN":["2194-5357","2194-5365"],"issn-type":[{"type":"print","value":"2194-5357"},{"type":"electronic","value":"2194-5365"}],"subject":[],"published":{"date-parts":[[2019,11,7]]},"assertion":[{"value":"7 November 2019","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICNC-FSKD","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"The International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Kunming","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"China","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":"20 July 2019","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"22 July 2019","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"icncfskd2019","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}