The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Comparing state-of-the-art evolutionary multi-objective algorithms for long-term groundwater monitoring design
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
A fast and elitist multiobjective genetic algorithm: NSGA-II
Deb, K., Pratap, A., Agarwal, S., & Meyarivan, T. (2002) · IEEE Transactions on Evolutionary Computation · doi:10.1109/4235.996017 · Cited by 50,053
Cited by
Maier, H. R., Kapelan, Z., Kasprzyk, J., Kollat, J., Matott, L. S., Cunha, M. C., Dandy, G. C., Gibbs, M. S., Keedwell, E., Marchi, A., et al. (2014) · Environmental Modelling & Software · doi:10.1016/j.envsoft.2014.09.013 · Cited by 657
Self-citationMany objective robust decision making for complex environmental systems undergoing change
Kasprzyk, J. R., Nataraj, S., Reed, P. M., & Lempert, R. J. (2013) · Environmental Modelling & Software · doi:10.1016/j.envsoft.2012.12.007 · Cited by 508
Self-citationA survey on multi-objective evolutionary algorithms for many-objective problems
von Lücken, C., Barán, B., & Brizuela, C. (2014) · Computational Optimization and Applications · doi:10.1007/s10589-014-9644-1 · Cited by 297
Exploratory modeling for analyzing coupled human-natural systems under uncertainty
Moallemi, E. A., Kwakkel, J., de Haan, F. J., & Bryan, B. A. (2020) · Global Environmental Change · doi:10.1016/j.gloenvcha.2020.102186 · Cited by 130
Hinds, C. A. (2016) · California Polytechnic State University (MSc Thesis) · doi:10.15368/theses.2014.189 · Cited by 1
Metadata
- Authors
- Kollat, J. B., & Reed, P. M.
- Venue
- Advances in Water Resources
- Publisher
- Elsevier BV
- Published
- 2006-06
- Volume
- 29
- Issue
- 6
- Pages
- 792-807
- ISSN
- 0309-1708 (ISSN-L)
- OpenAlex
- W2109443480
- Cited by
- 328
- References
- 1
- FWCI
- 6.59
- 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: Comparing state-of-the-art evolutionary multi-objective algorithms for long-term groundwater monitoring design. https://app.cochat.ai/papers/10.1016/j.advwatres.2005.07.010
- The paper
- Kollat, J. B., & Reed, P. M. (2006). Comparing state-of-the-art evolutionary multi-objective algorithms for long-term groundwater monitoring design. Advances in Water Resources. https://doi.org/10.1016/j.advwatres.2005.07.010
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.
