Heuristic principles for the design of artificial neural networks
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
High collinearity among input variables can result in model non-convergence, inconsistent results and degraded model performance.
“This can result in model non-convergence, inconsistent results and degraded model performance (Walczak & Cerpa 1999, Neumann 2002).”
From Comparison between environmental characteristics of larval bluefin tuna Thunnus thynnus habitat in the Gulf of Mexico and western Mediterranean Sea (2013) · cites this paper as Walczak & Cerpa 1999
Cited by
Sorted by citations
Muhling, B., Reglero, P., Ciannelli, L., Alvarez-Berastegui, D., Alemany, F., Lamkin, J., & Roffer, M. (2013) · Marine Ecology Progress Series · doi:10.3354/meps10397 · Cited by 58 · see citing works
Quantum computing and supervised machine learning
Oneto, L., Ridella, S., & Anguita, D. (2017) · Quantum Inspired Computational Intelligence · doi:10.1016/b978-0-12-804409-4.00002-4 · Cited by 11 · see citing works
- Authors
- Walczak, S., & Cerpa, N.
- Affiliations
- University of Colorado Denver (US)
- UNSW Sydney (AU)
- Corresponding author
- Walczak, Steven
- Venue
- Information and Software Technology
- Publisher
- Elsevier BV
- Published
- 1999-01
- Volume
- 41
- Issue
- 2
- Pages
- 107-117
- ISSN
- 0950-5849 (ISSN-L)
- OpenAlex
- W1985475871
- Cited by
- 195
- References
- 0
- Citations by year
- 2026: 1 · 2025: 8 · 2024: 11 · 2023: 7 · 2022: 15 · 2021: 11 · 2020: 10 · 2019: 13 · 2018: 8 · 2017: 10 · 2016: 9 · 2015: 9 · 2014: 7 · 2013: 12 · 2012: 7
- FWCI
- 4.14
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Information and Software Technology (publishedVersion)
- Digital Commons - University of South Florida (University of South Florida) (submittedVersion)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Neural Networks and Applications
- Physical Sciences › Computer Science › Artificial Intelligence › Machine Learning and ELM
- Physical Sciences › Computer Science › Artificial Intelligence › Artificial Intelligence Applications
- Keywords
- neural network design, domain knowledge, knowledge engineering, learning algorithm selection, factorial design
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.
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