The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
A general regression neural network
Abstract
A memory-based network that provides estimates of continuous variables and converges to the underlying (linear or nonlinear) regression surface is described. The general regression neural network (GRNN) is a one-pass learning algorithm with a highly parallel structure. It is shown that, even with sparse data in a multidimensional measurement space, the algorithm provides smooth transitions from one observed value to another. The algorithmic form can be used for any regression problem in which an assumption of linearity is not justified.
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Citations
Cites
Variable Kernel Estimates of Multivariate Densities
Breiman, L., Meisel, W., & Purcell, E. (1977) · Technometrics · doi:10.1080/00401706.1977.10489521 · Cited by 488
Cited by
A Survey of Convolutional Neural Networks: Analysis, Applications, and Prospects
Li, Z., Liu, F., Yang, W., Peng, S., & Zhou, J. (2022) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2021.3084827 · Cited by 5,273
“Chaotic neural networks [8] and A general regression neural network [9].”
BackgroundMachine Learning in Agriculture: A Review
Liakos, K., Busato, P., Moshou, D., Pearson, S., & Bochtis, D. (2018) · Sensors · doi:10.3390/s18082674 · Cited by 3,441
Fuzzy logic systems for engineering: a tutorial
Mendel, J. M. (1995) · Proceedings of the IEEE · doi:10.1109/5.364485 · Cited by 2,110
A new Fruit Fly Optimization Algorithm: Taking the financial distress model as an example
Pan, W.-T. (2012) · Knowledge-Based Systems · doi:10.1016/j.knosys.2011.07.001 · Cited by 1,543
Statistical and machine learning forecasting methods: Concerns and ways forward
Makridakis, S., Spiliotis, E., & Assimakopoulos, V. (2018) · PLOS ONE · doi:10.1371/journal.pone.0194889 · Cited by 1,528
Metadata
- Authors
- Specht, D. F.
- Venue
- IEEE Transactions on Neural Networks
- Published
- 1991
- Volume
- 2
- Issue
- 6
- Pages
- 568-576
- ISSN
- 1045-9227 (ISSN-L)
- OpenAlex
- W2149723649
- Cited by
- 4,492
- References
- 1
- FWCI
- 18.83
- Type
- journal article
- Language
- en
- Open access
- closed
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- Specht, D. F. (1991). A general regression neural network. IEEE Transactions on Neural Networks. https://doi.org/10.1109/72.97934
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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.
