The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Neuro-fuzzy modeling and control
Abstract
Fundamental and advanced developments in neuro-fuzzy synergisms for modeling and control are reviewed. The essential part of neuro-fuzzy synergisms comes from a common framework called adaptive networks, which unifies both neural networks and fuzzy models. The fuzzy models under the framework of adaptive networks is called adaptive-network-based fuzzy inference system (ANFIS), which possess certain advantages over neural networks. We introduce the design methods for ANFIS in both modeling and control applications. Current problems and future directions for neuro-fuzzy approaches are also addressed.>
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Citations
Cites
An Algorithm for Least-Squares Estimation of Nonlinear Parameters
Marquardt, D. W. (1963) · Journal of the Society for Industrial and Applied Mathematics · doi:10.1137/0111030 · Cited by 30,728
Cited by
Interval Type-2 Fuzzy Logic Systems Made Simple
Mendel, J. M., John, R. I., & Liu, F. (2006) · IEEE Transactions on Fuzzy Systems · doi:10.1109/tfuzz.2006.879986 · Cited by 2,112
Chen, W., Panahi, M., & Pourghasemi, H. R. (2017) · CATENA · doi:10.1016/j.catena.2017.05.034 · Cited by 325
Choubin, B., Darabi, H., Rahmati, O., Sajedi-Hosseini, F., & Kløve, B. (2018) · Science of The Total Environment · doi:10.1016/j.scitotenv.2017.09.293 · Cited by 292
Modeling and Simulation of an Adaptive Neuro-Fuzzy Inference System (ANFIS) for Mobile Learning
Al-Hmouz, A., Shen, J., Al-Hmouz, R., & Yan, J. (2012) · IEEE Transactions on Learning Technologies · doi:10.1109/tlt.2011.36 · Cited by 286
An analytical method for diseases prediction using machine learning techniques
Nilashi, M., Ibrahim, O. B., Ahmadi, H., & Shahmoradi, L. (2017) · Computers & Chemical Engineering · doi:10.1016/j.compchemeng.2017.06.011 · Cited by 190
Metadata
- Authors
- Jang, J.-S. R., & Sun, C.-T.
- Venue
- Proceedings of the IEEE
- Published
- 1995-03
- Volume
- 83
- Issue
- 3
- Pages
- 378-406
- ISSN
- 0018-9219 (ISSN-L)
- OpenAlex
- W2133321814
- Cited by
- 2,328
- References
- 1
- FWCI
- 41.17
- Type
- journal article
- Language
- en
- Open access
- closed
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- Jang, J.-S. R., & Sun, C.-T. (1995). Neuro-fuzzy modeling and control. Proceedings of the IEEE. https://doi.org/10.1109/5.364486
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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.
