The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.
Modeling of strength of high-performance concrete using artificial neural networks
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Citations
Cites
Parallel Distributed Processing: Explorations in the Microstructure of Cognition: Foundations
Rumelhart, D. E., McClelland, J. L., & AU (1986) · doi:10.7551/mitpress/5236.001.0001 · Cited by 15,686
Knowledge‐Based Modeling of Material Behavior with Neural Networks
Ghaboussi, J., Garrett, J. H., & Wu, X. (1991) · Journal of Engineering Mechanics · doi:10.1061/(asce)0733-9399(1991)117:1(132 · Cited by 775
HPC Strength Prediction Using Artificial Neural Network
Kasperkiewicz, J., Racz, J., & Dubrawski, A. (1995) · Journal of Computing in Civil Engineering · doi:10.1061/(asce)0887-3801(1995)9:4(279 · Cited by 241
Analysis of Concrete Strength Versus Water-Cement Ratio Relationship
Popovics, S. (1990) · ACI Materials Journal · doi:10.14359/1944 · Cited by 112
Some Engineering Properties of Slag Concrete as Influenced by Mix Proportioning and Curing
Swamy, R. N., & Bouikni, A. (1990) · ACI Materials Journal · doi:10.14359/2148 · Cited by 75
Cited by
Explaining Deep Neural Networks and Beyond: A Review of Methods and Applications
Samek, W., Montavon, G., Lapuschkin, S., Anders, C. J., & Muller, K.-R. (2021) · Proceedings of the IEEE · doi:10.1109/jproc.2021.3060483 · Cited by 1,477
“Concrete Compressive Strength Data set [197], displayed at”
BackgroundMethodInfluentialMachine Learning for Structural Engineering: A State-of-the-Art Review
Thai, H.-T. (2022) · Structures · doi:10.1016/j.istruc.2022.02.003 · Cited by 748
Golafshani, E. M., Behnood, A., & Arashpour, M. (2020) · Construction and Building Materials · doi:10.1016/j.conbuildmat.2019.117266 · Cited by 478
Young, B. A., Hall, A., Pilon, L., Gupta, P., & Sant, G. (2019) · Cement and Concrete Research · doi:10.1016/j.cemconres.2018.09.006 · Cited by 414
Zhang, J., Ma, G., Huang, Y., sun, J., Aslani, F., & Nener, B. (2019) · Construction and Building Materials · doi:10.1016/j.conbuildmat.2019.03.189 · Cited by 389
Metadata
- Authors
- Yeh, I.-C.
- Venue
- Cement and Concrete Research
- Publisher
- Elsevier BV
- Published
- 1998-12
- Volume
- 28
- Issue
- 12
- Pages
- 1797-1808
- ISSN
- 0008-8846 (ISSN-L)
- OpenAlex
- W2061933243
- Cited by
- 1,447
- References
- 5
- FWCI
- 2.08
- Type
- journal article
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: Modeling of strength of high-performance concrete using artificial neural networks. https://app.cochat.ai/papers/10.1016/s0008-8846(98)00165-3
- The paper
- Yeh, I.-C. (1998). Modeling of strength of high-performance concrete using artificial neural networks. Cement and Concrete Research. https://doi.org/10.1016/s0008-8846(98)00165-3
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
