The DOI matches its Crossref record; 68 of the 68 references it cites were found in a registry or an index.
A comparative study of ANN and ANFIS models for the prediction of cement-based mortar materials compressive strength
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Neural Networks: A Comprehensive Foundation
Haykin, S. (1998) · Cited by 30,070
ANFIS: adaptive-network-based fuzzy inference system
Jang, J.-S. R. (1993) · IEEE Transactions on Systems, Man, and Cybernetics · doi:10.1109/21.256541 · Cited by 16,254
Nazuno, J. F. (2000) · Computación y Sistemas · Cited by 3,201
Introduction to artificial neural systems
Żurada, J. M. (1992) · Medical Entomology and Zoology · Cited by 2,355
Neuro-fuzzy modeling and control
Jang, J.-S. R., & Sun, C.-T. (1995) · Proceedings of the IEEE · doi:10.1109/5.364486 · Cited by 2,328
Introduction to artificial neural systems
Nelson, D., & Wang, J. (1992) · Neurocomputing · doi:10.1016/0925-2312(92)90018-k · Cited by 1,999
Emerging Artificial Intelligence Methods in Structural Engineering
Salehi, H., & Burgueño, R. (2018) · Engineering Structures · doi:10.1016/j.engstruct.2018.05.084 · Cited by 1,068
Neural Networks in Civil Engineering: 1989–2000
Adeli, H. (2001) · Computer-Aided Civil and Infrastructure Engineering · doi:10.1111/0885-9507.00219 · Cited by 884
Neural Networks: Methodology and Applications
Dreyfus, G. (2010) · doi:10.1007/3-540-28847-3 · Cited by 581
Topçu, İ. B., & Sarıdemir, M. (2008) · Computational Materials Science · doi:10.1016/j.commatsci.2007.04.009 · Cited by 531
Cited by
Nguyen, Q. H., Ly, H.-B., Ho, L. S., Al-Ansari, N., Le, H. V., Tran, V. Q., Prakash, I., & Pham, B. T. (2021) · Mathematical Problems in Engineering · doi:10.1155/2021/4832864 · Cited by 624
Metadata
- Authors
- Armaghani, D. J., & Asteris, P. G.
- Venue
- Neural Computing and Applications
- Published
- 2020-08-10
- Volume
- 33
- Issue
- 9
- Pages
- 4501-4532
- ISSN
- 0941-0643 (ISSN-L)
- 1433-3058
- OpenAlex
- W3048264598
- Cited by
- 466
- References
- 68
- FWCI
- 29.71
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: A comparative study of ANN and ANFIS models for the prediction of cement-based mortar materials compressive strength. https://app.cochat.ai/papers/10.1007/s00521-020-05244-4
- The paper
- Armaghani, D. J., & Asteris, P. G. (2021). A comparative study of ANN and ANFIS models for the prediction of cement-based mortar materials compressive strength. Neural Computing and Applications. https://doi.org/10.1007/s00521-020-05244-4
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.
