{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,8]],"date-time":"2026-07-08T12:05:39Z","timestamp":1783512339103,"version":"3.55.0"},"reference-count":52,"publisher":"Springer Science and Business Media LLC","issue":"12","license":[{"start":{"date-parts":[[2019,6,14]],"date-time":"2019-06-14T00:00:00Z","timestamp":1560470400000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2019,6,14]],"date-time":"2019-06-14T00:00:00Z","timestamp":1560470400000},"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":["Neural Comput & Applic"],"published-print":{"date-parts":[[2020,6]]},"DOI":"10.1007\/s00521-019-04267-w","type":"journal-article","created":{"date-parts":[[2019,6,14]],"date-time":"2019-06-14T16:16:26Z","timestamp":1560528986000},"page":"7995-8010","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":131,"title":["Prediction of fresh and hardened properties of self-compacting concrete using support vector regression approach"],"prefix":"10.1007","volume":"32","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1238-5636","authenticated-orcid":false,"given":"Prasenjit","family":"Saha","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Prasenjit","family":"Debnath","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Paul","family":"Thomas","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2019,6,14]]},"reference":[{"key":"4267_CR1","doi-asserted-by":"publisher","first-page":"121","DOI":"10.1016\/j.conbuildmat.2014.04.048","volume":"64","author":"IP Sfikas","year":"2014","unstructured":"Sfikas IP, Badogiannis EG, Trezos KG (2014) Rheology and mechanical characteristics of self-compacting concrete mixtures containing metakaolin. Constr Build Mater 64:121\u2013129. \nhttps:\/\/doi.org\/10.1016\/j.conbuildmat.2014.04.048","journal-title":"Constr Build Mater"},{"key":"4267_CR2","doi-asserted-by":"publisher","first-page":"626","DOI":"10.1016\/j.conbuildmat.2014.09.071","volume":"73","author":"A Beycioglu","year":"2014","unstructured":"Beycioglu A, Yilmaz Aruntas H (2014) Workability and mechanical properties of self-compacting concretes containing LLFA, GBFS and MC. Constr Build Mater 73:626\u2013635. \nhttps:\/\/doi.org\/10.1016\/j.conbuildmat.2014.09.071","journal-title":"Constr Build Mater"},{"key":"4267_CR3","doi-asserted-by":"publisher","first-page":"1132","DOI":"10.1016\/j.conbuildmat.2015.05.021","volume":"93","author":"S-W Yoo","year":"2015","unstructured":"Yoo S-W, Ryu G-S, Choo JF (2015) Evaluation of the effects of high-volume fly ash on the flexural behavior of reinforced concrete beams. Constr Build Mater 93:1132\u20131144. \nhttps:\/\/doi.org\/10.1016\/j.conbuildmat.2015.05.021","journal-title":"Constr Build Mater"},{"key":"4267_CR4","doi-asserted-by":"publisher","first-page":"448","DOI":"10.1016\/j.conbuildmat.2015.07.081","volume":"94","author":"PK Acharya","year":"2015","unstructured":"Acharya PK, Patro SK (2015) Effect of lime and ferrochrome ash (FA) as partial replacement of cement on strength, ultrasonic pulse velocity and permeability of concrete. Constr Build Mater 94:448\u2013457. \nhttps:\/\/doi.org\/10.1016\/j.conbuildmat.2015.07.081","journal-title":"Constr Build Mater"},{"key":"4267_CR5","doi-asserted-by":"publisher","first-page":"90","DOI":"10.1016\/j.conbuildmat.2015.07.001","volume":"94","author":"M Jalal","year":"2015","unstructured":"Jalal M, Pouladkhan A, Fasihi O, Jafari D (2015) Comparative study on effects of Class F fly ash, nano silica and silica fume on properties of high performance self compacting concrete. Constr Build Mater 94:90\u2013104","journal-title":"Constr Build Mater"},{"key":"4267_CR6","doi-asserted-by":"publisher","first-page":"73","DOI":"10.1016\/j.conbuildmat.2011.10.035","volume":"29","author":"R Siddique","year":"2012","unstructured":"Siddique R, Aggarwal P, Aggarwal Y (2012) Influence of water\/powder ratio on strength properties of self-compacting concrete containing coal fly ash and bottom ash. Constr Build Mater 29:73\u201381. \nhttps:\/\/doi.org\/10.1016\/j.conbuildmat.2011.10.035","journal-title":"Constr Build Mater"},{"key":"4267_CR7","doi-asserted-by":"publisher","first-page":"1394","DOI":"10.1016\/j.conbuildmat.2007.04.005","volume":"22","author":"B Sukumar","year":"2008","unstructured":"Sukumar B, Nagamani K, Srinivasa Raghavan R (2008) Evaluation of strength at early ages of self-compacting concrete with high volume fly ash. Constr Build Mater 22:1394\u20131401. \nhttps:\/\/doi.org\/10.1016\/j.conbuildmat.2007.04.005","journal-title":"Constr Build Mater"},{"key":"4267_CR8","doi-asserted-by":"publisher","first-page":"350","DOI":"10.1016\/j.advengsoft.2008.05.002","volume":"40","author":"M Saridemir","year":"2009","unstructured":"Saridemir M (2009) Prediction of compressive strength of concretes containing metakaolin and silica fume by artificial neural networks. Adv Eng Softw 40:350\u2013355. \nhttps:\/\/doi.org\/10.1016\/j.advengsoft.2008.05.002","journal-title":"Adv Eng Softw"},{"key":"4267_CR9","doi-asserted-by":"publisher","first-page":"334","DOI":"10.1016\/j.advengsoft.2008.05.005","volume":"40","author":"C Bilim","year":"2009","unstructured":"Bilim C, Ati\u015f CD, Tanyildizi H, Karahan O (2009) Predicting the compressive strength of ground granulated blast furnace slag concrete using artificial neural network. Adv Eng Softw 40:334\u2013340. \nhttps:\/\/doi.org\/10.1016\/j.advengsoft.2008.05.005","journal-title":"Adv Eng Softw"},{"key":"4267_CR10","doi-asserted-by":"publisher","first-page":"856","DOI":"10.1016\/j.advengsoft.2009.01.005","volume":"40","author":"F \u00d6zcan","year":"2009","unstructured":"\u00d6zcan F, Ati\u015f CD, Karahan O et al (2009) Comparison of artificial neural network and fuzzy logic models for prediction of long-term compressive strength of silica fume concrete. Adv Eng Softw 40:856\u2013863. \nhttps:\/\/doi.org\/10.1016\/j.advengsoft.2009.01.005","journal-title":"Adv Eng Softw"},{"key":"4267_CR11","doi-asserted-by":"publisher","first-page":"133","DOI":"10.1007\/s00521-011-0671-x","volume":"22","author":"H Yaprak","year":"2013","unstructured":"Yaprak H, Karaci A, Demir I (2013) Prediction of the effect of varying cure conditions and w\/c ratio on the compressive strength of concrete using artificial neural networks. Neural Comput Appl 22:133\u2013141. \nhttps:\/\/doi.org\/10.1007\/s00521-011-0671-x","journal-title":"Neural Comput Appl"},{"key":"4267_CR12","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-012-1082-3","author":"A Nazari","year":"2012","unstructured":"Nazari A, Hajiallahyari H, Rahimi A et al (2012) Prediction compressive strength of Portland cement-based geopolymers by artificial neural networks. Neural Comput Appl. \nhttps:\/\/doi.org\/10.1007\/s00521-012-1082-3","journal-title":"Neural Comput Appl"},{"key":"4267_CR13","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-012-1085-0","author":"S Riahi","year":"2012","unstructured":"Riahi S, Nazari A (2012) Predicting the effects of nanoparticles on early age compressive strength of ash-based geopolymers by artificial neural networks. Neural Comput Appl. \nhttps:\/\/doi.org\/10.1007\/s00521-012-1085-0","journal-title":"Neural Comput Appl"},{"key":"4267_CR14","doi-asserted-by":"publisher","first-page":"1133","DOI":"10.1007\/s00521-012-0879-4","volume":"22","author":"S Suba\u015fi","year":"2013","unstructured":"Suba\u015fi S, Beycio\u01e7lu A, Sancak E, \u015eahin I (2013) Rule-based Mamdani type fuzzy logic model for the prediction of compressive strength of silica fume included concrete using non-destructive test results. Neural Comput Appl 22:1133\u20131139. \nhttps:\/\/doi.org\/10.1007\/s00521-012-0879-4","journal-title":"Neural Comput Appl"},{"key":"4267_CR15","doi-asserted-by":"publisher","first-page":"1005","DOI":"10.1007\/s00521-014-1763-1","volume":"26","author":"S Kosti\u0107","year":"2015","unstructured":"Kosti\u0107 S, Vasovi\u0107 D (2015) Prediction model for compressive strength of basic concrete mixture using artificial neural networks. Neural Comput Appl 26:1005\u20131024. \nhttps:\/\/doi.org\/10.1007\/s00521-014-1763-1","journal-title":"Neural Comput Appl"},{"key":"4267_CR16","doi-asserted-by":"publisher","first-page":"707","DOI":"10.1007\/s00521-016-2368-7","volume":"28","author":"O Belalia Douma","year":"2016","unstructured":"Belalia Douma O, Boukhatem B, Ghrici M, Tagnit-Hamou A (2016) Prediction of properties of self-compacting concrete containing fly ash using artificial neural network. Neural Comput Appl 28:707\u2013718. \nhttps:\/\/doi.org\/10.1007\/s00521-016-2368-7","journal-title":"Neural Comput Appl"},{"key":"4267_CR17","doi-asserted-by":"publisher","first-page":"55","DOI":"10.1016\/j.conbuildmat.2015.12.035","volume":"106","author":"M Sonebi","year":"2016","unstructured":"Sonebi M, Cevik A, Gr\u00fcnewald S, Walraven J (2016) Modelling the fresh properties of self-compacting concrete using support vector machine approach. Constr Build Mater 106:55\u201364. \nhttps:\/\/doi.org\/10.1016\/j.conbuildmat.2015.12.035","journal-title":"Constr Build Mater"},{"key":"4267_CR18","doi-asserted-by":"publisher","first-page":"299","DOI":"10.12989\/cac.2007.4.4.299","volume":"4","author":"JJ Lee","year":"2007","unstructured":"Lee JJ, Kim DK, Chang SK, Lee J-H (2007) Application of support vector regression for the prediction of concrete strength. Comput Concr 4:299\u2013316","journal-title":"Comput Concr"},{"key":"4267_CR19","doi-asserted-by":"publisher","first-page":"170","DOI":"10.4028\/www.scientific.net\/AMM.438-439.170","volume":"438\u2013439","author":"HY Yang","year":"2013","unstructured":"Yang HY, Dong YF (2013) Modelling concrete strength using support vector machines. Appl Mech Mater 438\u2013439:170\u2013173. \nhttps:\/\/doi.org\/10.4028\/www.scientific.net\/AMM.438-439.170","journal-title":"Appl Mech Mater"},{"key":"4267_CR20","doi-asserted-by":"publisher","first-page":"9","DOI":"10.1061\/(ASCE)MT.1943-5533.0000507","volume":"25","author":"JS Yazdi","year":"2013","unstructured":"Yazdi JS, Kalantary F, Yazdi HS (2013) Prediction of elastic modulus of concrete using support vector committee method. J Mater Civ Eng 25:9\u201320. \nhttps:\/\/doi.org\/10.1061\/(ASCE)MT.1943-5533.0000507","journal-title":"J Mater Civ Eng"},{"key":"4267_CR21","doi-asserted-by":"publisher","first-page":"1479","DOI":"10.1016\/j.conbuildmat.2010.01.006","volume":"24","author":"K Yan","year":"2010","unstructured":"Yan K, Shi C (2010) Prediction of elastic modulus of normal and high strength concrete by support vector machine. Constr Build Mater 24:1479\u20131485. \nhttps:\/\/doi.org\/10.1016\/j.conbuildmat.2010.01.006","journal-title":"Constr Build Mater"},{"key":"4267_CR22","doi-asserted-by":"publisher","first-page":"589","DOI":"10.1016\/j.conbuildmat.2017.03.124","volume":"143","author":"F Naseri","year":"2017","unstructured":"Naseri F, Jafari F, Mohseni E et al (2017) Experimental observations and SVM-based prediction of properties of polypropylene fibres reinforced self-compacting composites incorporating nano-CuO. Constr Build Mater 143:589\u2013598. \nhttps:\/\/doi.org\/10.1016\/j.conbuildmat.2017.03.124","journal-title":"Constr Build Mater"},{"key":"4267_CR23","doi-asserted-by":"publisher","first-page":"169","DOI":"10.1016\/j.ijprt.2016.06.003","volume":"9","author":"J Liu","year":"2016","unstructured":"Liu J, Yan KZ, Zhao X, Hu Y (2016) Prediction of autogenous shrinkage of concretes by support vector machine. Int J Pavement Res Technol 9:169\u2013177. \nhttps:\/\/doi.org\/10.1016\/j.ijprt.2016.06.003","journal-title":"Int J Pavement Res Technol"},{"key":"4267_CR24","doi-asserted-by":"publisher","first-page":"337","DOI":"10.12989\/cac.2013.11.4.337","volume":"11","author":"J Sobhani","year":"2013","unstructured":"Sobhani J, Khanzadi M, Movahedian AH (2013) Support vector machine for prediction of the compressive strength of no-slump concrete. Comput Concr 11:337\u2013350. \nhttps:\/\/doi.org\/10.12989\/cac.2013.11.4.337","journal-title":"Comput Concr"},{"key":"4267_CR25","doi-asserted-by":"publisher","first-page":"886","DOI":"10.1016\/j.jsv.2007.09.054","volume":"311","author":"D Yinfeng","year":"2008","unstructured":"Yinfeng D, Yingmin L, Ming L, Mingkui X (2008) Nonlinear structural response prediction based on support vector machines. J Sound Vib 311:886\u2013897. \nhttps:\/\/doi.org\/10.1016\/j.jsv.2007.09.054","journal-title":"J Sound Vib"},{"key":"4267_CR26","doi-asserted-by":"publisher","first-page":"205","DOI":"10.1016\/j.asoc.2014.11.014","volume":"27","author":"A Saber Mahani","year":"2015","unstructured":"Saber Mahani A, Shojaee S, Salajegheh E, Khatibinia M (2015) Hybridizing two-stage meta-heuristic optimization model with weighted least squares support vector machine for optimal shape of double-arch dams. Appl Soft Comput J 27:205\u2013218. \nhttps:\/\/doi.org\/10.1016\/j.asoc.2014.11.014","journal-title":"Appl Soft Comput J"},{"key":"4267_CR27","doi-asserted-by":"publisher","first-page":"1556","DOI":"10.4028\/www.scientific.net\/AMM.578-579.1556","volume":"578\u2013579","author":"S Yang","year":"2014","unstructured":"Yang S, Fang CQ, Yuan ZJ (2014) Study on mechanical properties of corroded reinforced concrete using support vector machines. Appl Mech Mater 578\u2013579:1556\u20131561. \nhttps:\/\/doi.org\/10.4028\/www.scientific.net\/AMM.578-579.1556","journal-title":"Appl Mech Mater"},{"key":"4267_CR28","doi-asserted-by":"publisher","first-page":"704","DOI":"10.1016\/j.jhydrol.2006.01.021","volume":"328","author":"PS Yu","year":"2006","unstructured":"Yu PS, Chen ST, Chang IF (2006) Support vector regression for real-time flood stage forecasting. J Hydrol 328:704\u2013716. \nhttps:\/\/doi.org\/10.1016\/j.jhydrol.2006.01.021","journal-title":"J Hydrol"},{"key":"4267_CR29","doi-asserted-by":"publisher","first-page":"29","DOI":"10.1016\/j.engfracmech.2012.11.014","volume":"98","author":"P Yuvaraj","year":"2013","unstructured":"Yuvaraj P, Ramachandra Murthy A, Iyer NR et al (2013) Support vector regression based models to predict fracture characteristics of high strength and ultra high strength concrete beams. Eng Fract Mech 98:29\u201343. \nhttps:\/\/doi.org\/10.1016\/j.engfracmech.2012.11.014","journal-title":"Eng Fract Mech"},{"key":"4267_CR30","doi-asserted-by":"publisher","first-page":"621","DOI":"10.1016\/j.jhydrol.2006.04.030","volume":"330","author":"S Tripathi","year":"2006","unstructured":"Tripathi S, Srinivas VV, Nanjundiah RS (2006) Downscaling of precipitation for climate change scenarios: a support vector machine approach. J Hydrol 330:621\u2013640. \nhttps:\/\/doi.org\/10.1016\/j.jhydrol.2006.04.030","journal-title":"J Hydrol"},{"key":"4267_CR31","doi-asserted-by":"publisher","first-page":"599","DOI":"10.1623\/hysj.51.4.599","volume":"51","author":"J-Y Lin","year":"2006","unstructured":"Lin J-Y, Cheng C-T, Chau K-W (2006) Using support vector machines for long-term discharge prediction. Hydrol Sci J 51:599\u2013612. \nhttps:\/\/doi.org\/10.1623\/hysj.51.4.599","journal-title":"Hydrol Sci J"},{"key":"4267_CR32","doi-asserted-by":"publisher","first-page":"128","DOI":"10.1016\/j.jhydrol.2010.11.002","volume":"396","author":"H Yoon","year":"2011","unstructured":"Yoon H, Jun SC, Hyun Y et al (2011) A comparative study of artificial neural networks and support vector machines for predicting groundwater levels in a coastal aquifer. J Hydrol 396:128\u2013138. \nhttps:\/\/doi.org\/10.1016\/j.jhydrol.2010.11.002","journal-title":"J Hydrol"},{"key":"4267_CR33","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1061\/(ASCE)GM.1943-5622.0001067","volume":"18","author":"P Debnath","year":"2017","unstructured":"Debnath P, Dey AK (2017) Prediction of bearing capacity of geogrid-reinforced stone columns using support vector regression. Int J Geomech 18:1\u201315. \nhttps:\/\/doi.org\/10.1061\/(ASCE)GM.1943-5622.0001067","journal-title":"Int J Geomech"},{"key":"4267_CR34","series-title":"Advances in neural information processing systems","volume-title":"Support vector method for function approximation, regression estimation, and signal processing","author":"VN Vapnik","year":"1996","unstructured":"Vapnik VN, Golowich SE, Smola A (1996) Support vector method for function approximation, regression estimation, and signal processing. Advances in neural information processing systems, Morgan Kaufmann, San Mateo"},{"key":"4267_CR35","first-page":"281","volume-title":"Advances in neural information processing systems","author":"V Vapnik","year":"1997","unstructured":"Vapnik V, Golowich S, Smola A (1997) Support vector method for function approximation, regression estimation, and signalprocessing. In: Advances in neural information processing systems. MIT Press, Cambridge, pp 281\u2013287"},{"key":"4267_CR36","unstructured":"Gunn SR (2001) Support vector machines for classification and regression. In: Technical report. University of Southampton, Southampton. \nhttp:\/\/www.isis.ecs.soton.ac.uk\/isystems\/kernel\/svm.zip\n\n. Accessed 16 May 2018"},{"key":"4267_CR37","doi-asserted-by":"publisher","unstructured":"Hillier FS, Editor S, Quantitative C, et al (2008) Linear and Nonlinear Programming. \nhttps:\/\/doi.org\/10.1007\/978-0-387-74503-9","DOI":"10.1007\/978-0-387-74503-9"},{"key":"4267_CR38","doi-asserted-by":"crossref","unstructured":"Vapnik VN, Jordan M, F- J (2000)The nature of statistical learning theory. Springer, New York. ISBN 0-387-98780-0, SPIN 10713304","DOI":"10.1007\/978-1-4757-3264-1"},{"key":"4267_CR39","doi-asserted-by":"publisher","first-page":"199","DOI":"10.1023\/B:Stco.0000035301.49549.88","volume":"14","author":"AJJ Smola","year":"2004","unstructured":"Smola AJJ, Sch\u00f6lkopf B (2004) A tutorial on support vector regression. Stat Comput 14:199\u2013222. \nhttps:\/\/doi.org\/10.1023\/B:Stco.0000035301.49549.88","journal-title":"Stat Comput"},{"key":"4267_CR40","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-017-3104-7","author":"CK Ma","year":"2017","unstructured":"Ma CK, Lee YH, Awang AZ et al (2017) Artificial neural network models for FRP-repaired concrete subjected to pre-damaged effects. Neural Comput Appl. \nhttps:\/\/doi.org\/10.1007\/s00521-017-3104-7","journal-title":"Neural Comput Appl"},{"key":"4267_CR41","doi-asserted-by":"publisher","first-page":"99","DOI":"10.1016\/j.cemconcomp.2008.12.003","volume":"31","author":"M Sahmaran","year":"2009","unstructured":"Sahmaran M, Yaman I, Tokyay M (2009) Transport and mechanical properties of self consolidating concrete with high volume fly ash. Cem Concr Compos 31:99\u2013106. \nhttps:\/\/doi.org\/10.1016\/j.cemconcomp.2008.12.003","journal-title":"Cem Concr Compos"},{"key":"4267_CR42","doi-asserted-by":"publisher","first-page":"780","DOI":"10.1016\/j.advengsoft.2011.05.016","volume":"42","author":"R Siddique","year":"2011","unstructured":"Siddique R, Aggarwal P, Aggarwal Y (2011) Prediction of compressive strength of self-compacting concrete containing bottom ash using artificial neural networks. Adv Eng Softw 42:780\u2013786. \nhttps:\/\/doi.org\/10.1016\/j.advengsoft.2011.05.016","journal-title":"Adv Eng Softw"},{"key":"4267_CR43","doi-asserted-by":"publisher","first-page":"771","DOI":"10.1016\/j.cemconcomp.2011.04.005","volume":"33","author":"M Uysal","year":"2011","unstructured":"Uysal M, Yilmaz K (2011) Effect of mineral admixtures on properties of self-compacting concrete. Cem Concr Compos 33:771\u2013776. \nhttps:\/\/doi.org\/10.1016\/j.cemconcomp.2011.04.005","journal-title":"Cem Concr Compos"},{"key":"4267_CR44","unstructured":"Patel R (2003) Development of statistical models to simulate and optimize self-consolidating concrete mixes incorporating high volume of fly ash. Dissertation, University of Ryerson, Toronto"},{"key":"4267_CR45","unstructured":"Gettu R, Izquierdo J, Gomes PCC, Josa A (2002) Development of high-strength self-compacting concrete with fly ash: a four-step experimental methodology. In: Proceedings of the 27th conference on our world in concrete and structures, Paramasivam y TH Tan, Singapore, pp 217\u2013224"},{"key":"4267_CR46","doi-asserted-by":"publisher","first-page":"1878","DOI":"10.1016\/j.conbuildmat.2010.04.015","volume":"24","author":"E G\u00fcneyisi","year":"2010","unstructured":"G\u00fcneyisi E, Gesolu M, \u00d6zbay E (2010) Strength and drying shrinkage properties of self-compacting concretes incorporating multi-system blended mineral admixtures. Constr Build Mater 24:1878\u20131887. \nhttps:\/\/doi.org\/10.1016\/j.conbuildmat.2010.04.015","journal-title":"Constr Build Mater"},{"key":"4267_CR47","doi-asserted-by":"publisher","first-page":"82","DOI":"10.1016\/j.conbuildmat.2014.04.021","volume":"64","author":"MCS Nepomuceno","year":"2014","unstructured":"Nepomuceno MCS, Pereira-De-Oliveira LA, Lopes SMR (2014) Methodology for the mix design of self-compacting concrete using different mineral additions in binary blends of powders. Constr Build Mater 64:82\u201394. \nhttps:\/\/doi.org\/10.1016\/j.conbuildmat.2014.04.021","journal-title":"Constr Build Mater"},{"key":"4267_CR48","doi-asserted-by":"publisher","first-page":"12","DOI":"10.1016\/j.matdes.2013.03.106","volume":"51","author":"AF Bingol","year":"2013","unstructured":"Bingol AF, Tohumcu I (2013) Effects of different curing regimes on the compressive strength properties of self compacting concrete incorporating fly ash and silica fume. Mater Des 51:12\u201318. \nhttps:\/\/doi.org\/10.1016\/j.matdes.2013.03.106","journal-title":"Mater Des"},{"key":"4267_CR49","unstructured":"Krishnapal P, Yadav RK, Rajeev C (2013) Strength characteristics of self compacting concrete containing flyash. Res J Eng Sci. ISSN 2278:9472"},{"key":"4267_CR50","first-page":"342","volume":"7","author":"S Dhiyaneshwaran","year":"2013","unstructured":"Dhiyaneshwaran S, Ramanathan P, Baskar I, Venkatasubramani R (2013) Study on durability characteristics of self-compacting concrete with fly ash. Jordan J Civ Eng 7:342\u2013353","journal-title":"Jordan J Civ Eng"},{"key":"4267_CR51","unstructured":"Mahalingam B, Nagamani K (2011) Effect of processed fly ash on fresh and hardened properties of self compacting concrete. Int J Earth Sci Eng 4(5):930\u2013940. ISSN 0974-5904"},{"key":"4267_CR52","unstructured":"Muthupriya P, Sri PN, Ramanathan MP, Venkatasubramani R (2012) Strength and workability character of self compacting concrete with GGBFS, FA and SF. Int J Emerg Trends Eng Dev 2(2):424\u2013434. ISSN 2249-6149"}],"container-title":["Neural Computing and Applications"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-019-04267-w.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s00521-019-04267-w\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-019-04267-w.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,6,13]],"date-time":"2020-06-13T08:06:55Z","timestamp":1592035615000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s00521-019-04267-w"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,6,14]]},"references-count":52,"journal-issue":{"issue":"12","published-print":{"date-parts":[[2020,6]]}},"alternative-id":["4267"],"URL":"https:\/\/doi.org\/10.1007\/s00521-019-04267-w","relation":{},"ISSN":["0941-0643","1433-3058"],"issn-type":[{"value":"0941-0643","type":"print"},{"value":"1433-3058","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,6,14]]},"assertion":[{"value":"26 October 2017","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"21 May 2019","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"14 June 2019","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Compliance with ethical standards"}},{"value":"The author declares that they have no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}