Lin et al., 2008 - Google Patents
A hybrid of cooperative particle swarm optimization and cultural algorithm for neural fuzzy networks and its prediction applicationsLin et al., 2008
View PDF- Document ID
- 5357418945370617103
- Author
- Lin C
- Chen C
- Lin C
- Publication year
- Publication venue
- IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews)
External Links
Snippet
This study presents an evolutionary neural fuzzy network, designed using the functional-link- based neural fuzzy network (FLNFN) and a new evolutionary learning algorithm. This new evolutionary learning algorithm is based on a hybrid of cooperative particle swarm …
- 239000002245 particle 0 title abstract description 67
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- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computer systems based on biological models
- G06N3/02—Computer systems based on biological models using neural network models
- G06N3/06—Physical realisation, i.e. hardware implementation of neural networks, neurons or parts of neurons
- G06N3/063—Physical realisation, i.e. hardware implementation of neural networks, neurons or parts of neurons using electronic means
- G06N3/0635—Physical realisation, i.e. hardware implementation of neural networks, neurons or parts of neurons using electronic means using analogue means
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- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
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- G06N3/00—Computer systems based on biological models
- G06N3/02—Computer systems based on biological models using neural network models
- G06N3/08—Learning methods
- G06N3/082—Learning methods modifying the architecture, e.g. adding or deleting nodes or connections, pruning
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- G—PHYSICS
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- G06N3/02—Computer systems based on biological models using neural network models
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- G06N3/0454—Architectures, e.g. interconnection topology using a combination of multiple neural nets
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- G—PHYSICS
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- G05B13/00—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
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- G06N99/00—Subject matter not provided for in other groups of this subclass
- G06N99/005—Learning machines, i.e. computer in which a programme is changed according to experience gained by the machine itself during a complete run
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- G—PHYSICS
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- G06N5/02—Knowledge representation
- G06N5/022—Knowledge engineering, knowledge acquisition
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- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
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- G05B13/00—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
- G05B13/02—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
- G05B13/0265—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric the criterion being a learning criterion
- G05B13/0285—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric the criterion being a learning criterion using neural networks and fuzzy logic
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