A methodology using fuzzy logic to optimize feedforward artificial neural network configurations
- 1 May 1994
- journal article
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Systems, Man, and Cybernetics
- Vol. 24 (5), 760-768
- https://doi.org/10.1109/21.293489
Abstract
No abstract availableThis publication has 28 references indexed in Scilit:
- Sensitivity analysis of multilayer perceptron with differentiable activation functionsIEEE Transactions on Neural Networks, 1992
- A neural network approach to real-time condition monitoring of induction motorsIEEE Transactions on Industrial Electronics, 1991
- A simple method to derive bounds on the size and to train multilayer neural networksIEEE Transactions on Neural Networks, 1991
- Bounds on the number of hidden neurons in multilayer perceptronsIEEE Transactions on Neural Networks, 1991
- Methodology for on-line incipient fault detection in single-phase squirrel-cage induction motors using artificial neural networksIEEE Transactions on Energy Conversion, 1991
- Benefits of gain: speeded learning and minimal hidden layers in back-propagation networksIEEE Transactions on Systems, Man, and Cybernetics, 1991
- Fuzzy logic in control systems: fuzzy logic controller. IIEEE Transactions on Systems, Man, and Cybernetics, 1990
- Fuzzy logic in control systems: fuzzy logic controller. IIIEEE Transactions on Systems, Man, and Cybernetics, 1990
- What Size Net Gives Valid Generalization?Neural Computation, 1989
- The concept of a linguistic variable and its application to approximate reasoning—IInformation Sciences, 1975