{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,8]],"date-time":"2026-06-08T15:55:28Z","timestamp":1780934128073,"version":"3.54.1"},"reference-count":26,"publisher":"Springer Science and Business Media LLC","issue":"11","license":[{"start":{"date-parts":[[2020,9,19]],"date-time":"2020-09-19T00:00:00Z","timestamp":1600473600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2020,9,19]],"date-time":"2020-09-19T00:00:00Z","timestamp":1600473600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Neural Comput & Applic"],"published-print":{"date-parts":[[2022,6]]},"DOI":"10.1007\/s00521-020-05305-8","type":"journal-article","created":{"date-parts":[[2020,9,19]],"date-time":"2020-09-19T14:02:44Z","timestamp":1600524164000},"page":"8355-8363","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":78,"title":["Effect of number of neurons and layers in an artificial neural network for generalized concrete mix design"],"prefix":"10.1007","volume":"34","author":[{"given":"Mohammad","family":"Adil","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rahat","family":"Ullah","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5065-8714","authenticated-orcid":false,"given":"Salma","family":"Noor","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Neelam","family":"Gohar","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2020,9,19]]},"reference":[{"key":"5305_CR1","unstructured":"ACI Committee 211.1, Standard Practice for Selecting Proportions of Normal, Heavyweight, and Mass Concrete, part 1, ACI Manual of Concrete Practice, 2014."},{"key":"5305_CR2","unstructured":"ACI Committee 211.2, Standard Practice for Selecting Proportions for Structural Lightweight Concrete, part 2, ACI Manual of Concrete Practice, 1990."},{"key":"5305_CR3","unstructured":"ACI Committee 211. 3R-02: Guide for Selecting Proportions for No-Slump Concrete, part 3, ACI Manual of Concrete Practice, 2009."},{"key":"5305_CR4","unstructured":"ACI Committee 211. 3R-02: Guide for Selecting Proportions for No-Slump Concrete, part 3, ACI Manual of Concrete Practice, 2009., part 4, ACI Manual of Concrete Practice, 2009."},{"key":"5305_CR5","unstructured":"BS 5328\u2014Concrete, Part 2, Methods for Specifying Concrete Mixes., 2018"},{"key":"5305_CR6","first-page":"675","volume-title":"\u201cDetermining Optimum Structure for Artificial Neural Networks\u201d, 25th Annual Technical Conference and Exhibition of the Remote Sensing Society","author":"Taskin Kavzoglu","year":"1999","unstructured":"Kavzoglu Taskin (1999) \u201cDetermining Optimum Structure for Artificial Neural Networks\u201d, 25th Annual Technical Conference and Exhibition of the Remote Sensing Society. Cardiff, UK, pp 675\u2013682"},{"key":"5305_CR7","unstructured":"Shibata, Katsunari, and Yusuke Ikeda. \u201cEffect of number of hidden neurons on learning in large-scale layered neural networks.\u201d 2009 ICCAS-SICE. IEEE, 2009."},{"key":"5305_CR8","doi-asserted-by":"crossref","unstructured":"Fumumoto, Yuta, Shotaro Owaki, and Moriya Nakamura. \u201cEffect of number of neurons of a neural-network on compensation performance of SPM non-linear waveform distortion.\u201d 2017 Opto-Electronics and Communications Conference (OECC) and Photonics Global Conference (PGC). IEEE, 2017.","DOI":"10.1109\/OECC.2017.8114880"},{"key":"5305_CR9","doi-asserted-by":"crossref","unstructured":"Shafi, Imran, et al. \u201cImpact of varying neurons and hidden layers in neural network architecture for a time frequency application.\u201d 2006 IEEE International Multitopic Conference. IEEE, 2006.","DOI":"10.1109\/INMIC.2006.358160"},{"key":"5305_CR10","doi-asserted-by":"crossref","unstructured":"Sheela, K. Gnana, and Subramaniam N. Deepa. \u201cReview on methods to fix number of hidden neurons in neural networks.\u201d Mathematical Problems in Engineering 2013 (2013).","DOI":"10.1155\/2013\/425740"},{"key":"5305_CR11","unstructured":"Anthony N. Burkett (1991) \u201cOptimization of the Architecture of Feed-forward Neural Networks with Hidden Layers by Unit Elimination\u201d, Complex Systems, pp. 371 -380."},{"key":"5305_CR12","doi-asserted-by":"crossref","unstructured":". C Carpenter, William et al. (1994) \u201cCommon misconceptions about neural networks as approximators\u201d. Journal of Computing in Civil Engineering, pp. 345-358.","DOI":"10.1061\/(ASCE)0887-3801(1994)8:3(345)"},{"key":"5305_CR13","unstructured":"Saurabh Karsoliya (2012) \u201cApproximating Number of Hidden layer neurons in Multiple Hidden Layer BPNN Architecture\u201d, International Journal of Engineering Trends and Technology- Volume3 Issue 6."},{"key":"5305_CR14","doi-asserted-by":"crossref","unstructured":"L. Prechelt (1998) \u201cEarly stopping \u2013 but when\u201d, Neural Networks: Tricks of the trade, Lecture Notes in Computer Science, Springer Verlag, Heidelberg.","DOI":"10.1007\/3-540-49430-8_3"},{"key":"5305_CR15","doi-asserted-by":"crossref","unstructured":"R. Setiono (2001) \u201cFeed forward neural network construction using cross validation\u201d, Neural Computation, pp. 2865-2877.","DOI":"10.1162\/089976601317098565"},{"key":"5305_CR16","unstructured":"Noguchi T (1993) Relationship between compressive strength and modulus of elasticity of high-strength concrete. In Proceedings: the third international symposium on utilization of high strength concrete, symposium in Lillehammer, Norway, pp 1247\u20131254"},{"key":"5305_CR17","unstructured":"I-Cheng Yeh (1999), \u201cDesign of High Performance Concrete (HPC), mixture using Neural Networks and Nonlinear programming\u201d, Journal of Computing in Civil Engineering, Vol. 13, ASCE, ISSN 0877-3801\/99\/0001-0036\u20130042."},{"issue":"8","key":"5305_CR18","doi-asserted-by":"publisher","first-page":"1256","DOI":"10.3390\/ma12081256","volume":"12","author":"P Ziolkowski","year":"2019","unstructured":"Ziolkowski P, Niedostatkiewicz M (2019) Machine Learning Techniques in Concrete Mix Design. Materials 12(8):1256. https:\/\/doi.org\/10.3390\/ma12081256","journal-title":"Materials"},{"key":"5305_CR19","unstructured":"Amer Hasan Taher,Layth A. Al-Jaberi And Ahmed Mancy Mosa,(2018) Artificial Neural Network For Mix Proportioning Optimization Of Reactive Powder Concrete. Available from: .Journal of Theoretical and Applied Information Technology, 15th December 2018. Vol.96. No 23"},{"key":"5305_CR20","doi-asserted-by":"publisher","unstructured":"Ching-Yun Kao, Chin-Hung Shen, Jing-Chi Jan and Shih-Lin Hung, (2018), Computer-Aided Approach to Pozzolanic Concrete Mix Design, Hindawi, Advances in Civil Engineering, Volume 2018, Article ID 4398017, 15 pages, https:\/\/doi.org\/10.1155\/2018\/4398017","DOI":"10.1155\/2018\/4398017"},{"key":"5305_CR21","doi-asserted-by":"publisher","first-page":"379","DOI":"10.1016\/j.cemconres.2018.09.006","volume":"115","author":"BA Young","year":"2019","unstructured":"Young BA, Hall A, Pilon L, Gupta P, Sant G (2019) Can the compressive strength of concrete be estimated from knowledge of the mixture proportions?: New insights from statistical analysis and machine learning methods. Cement and Concrete Research 115:379\u2013388. https:\/\/doi.org\/10.1016\/j.cemconres.2018.09.006","journal-title":"Cement and Concrete Research"},{"key":"5305_CR22","doi-asserted-by":"crossref","unstructured":"Merve A\u00e7ikgen\u00e7 et al. (2015), \u201cUsing an Artificial Neural Network to Predict mix compositions of Steel Fiber-Reinforced Concrete\u201d, Arabian journal of Science and Engineering, pp. 407-419.","DOI":"10.1007\/s13369-014-1549-x"},{"key":"5305_CR23","unstructured":"Sourav Das (2015), Prediction of Concrete Mix Proportion using ANN Technique, International Research Journal of Engineering and Technology (IRJET), Volume: 02."},{"key":"5305_CR24","unstructured":"Sh.Charhate, M.Subhedar and N.Adsul, (2018) Prediction of Concrete Properties Using Multiple Linear Regression and Artificial Neural Network, Journal of Soft Computing in Civil Engineering, 2-3(2018) 27-38 http:\/\/dx.doi.org\/10.22115\/SCCE.2018.112140.1041"},{"key":"5305_CR25","unstructured":"civilengradil. (2020, July 24). civilengradil\/ANN-universal-concrete-mix-design: Release 1 of ANN Universal Mix Design tool (Version v1.0.0). Zenodo. http:\/\/doi.org\/10.5281\/zenodo.3959357"},{"key":"5305_CR26","doi-asserted-by":"publisher","first-page":"533","DOI":"10.1038\/323533a0","volume":"323","author":"David E Rumehart","year":"1986","unstructured":"Rumehart David E et al (1986) Learning representations by back propagating errors. Letters to nature 323:533\u2013536","journal-title":"Letters to nature"}],"container-title":["Neural Computing and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-020-05305-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00521-020-05305-8\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-020-05305-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,5,14]],"date-time":"2022-05-14T05:30:44Z","timestamp":1652506244000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00521-020-05305-8"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,9,19]]},"references-count":26,"journal-issue":{"issue":"11","published-print":{"date-parts":[[2022,6]]}},"alternative-id":["5305"],"URL":"https:\/\/doi.org\/10.1007\/s00521-020-05305-8","relation":{},"ISSN":["0941-0643","1433-3058"],"issn-type":[{"value":"0941-0643","type":"print"},{"value":"1433-3058","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,9,19]]},"assertion":[{"value":"15 May 2020","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"18 August 2020","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"19 September 2020","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}