POPFNN-CRI(S) : a fuzzy neural network based on the compositional rule of inference
Fuzzy Neural Networks are hybrid systems that combine the human inference style and natural language description of fuzzy systems with the learning and parallel processing of neural networks. A novel FNN architecture, an improved selforganizing neural network algorithm and two novel fuzzy members...
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| 格式: | Theses and Dissertations |
| 語言: | English |
| 出版: |
2011
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| 主題: | |
| 在線閱讀: | http://hdl.handle.net/10356/42627 |
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| 總結: | Fuzzy Neural Networks are hybrid systems that combine the human inference style
and natural language description of fuzzy systems with the learning and parallel
processing of neural networks. A novel FNN architecture, an improved selforganizing
neural network algorithm and two novel fuzzy membership function identification algorithms are proposed. They are the Pseudo Outer-Product based Fuzzy Neural Network using the Compositional Rule of Inference and a Singleton Fuzzifier (POPFNN-CRI(S)), the Modified Learning Vector Quantization (MLVQ) algorithm, the Fuzzy Kohonen Partition (FKP) and the Pseudo Fuzzy Kohonen
Partition (PFKP) algorithms. |
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