| 一种新型区间二型模糊神经网络隶属函数的设计 |
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| 作者姓名： | Wang Jiajun |
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| 作者单位： | 1.杭州电子科技大学自动化学院 杭州 310018 |
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| 基金项目： | the National Natural Science Foundation of China61273086 |
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| 摘 要： | 对于区间二型模糊神经网络（IT2FNN），论文给出了一种新型的模糊隶属函数（FMF）设计方法.通过所设计的模糊隶属函数，可以衍生出三种区间二型模糊隶属函数（IT2FMF）.每种区间二型模糊隶属函数都具有不同的不确定域.论文将三种衍生模糊隶属函数应用于简化区间二型模糊神经网络辨识两个非线性系统.通过仿真，将衍生区间二型模糊隶属函数的辨识性能与高斯和椭圆型模糊隶属函数进行了对比.仿真结果表明，通过调节简化区间二型模糊神经网络的参数，本文所设计的区间二型模糊隶属函数比高斯和椭圆型模糊隶属函数具有更好的辨识性能.
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| 关 键 词： | 模糊隶属函数(FMF) 区间二型模糊神经网络(IT2FNN) 非线性系统 系统辨识 |
| 收稿时间： | 2015-11-18 |
A New Type of Fuzzy Membership Function Designed for Interval Type-2 Fuzzy Neural Network |
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| Wang Jiajun.A New Type of Fuzzy Membership Function Designed for Interval Type-2 Fuzzy Neural Network[J].Acta Automatica Sinica,2017,43(8):1425-1433. |
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| Affiliation: | 1.School of Automation, Hangzhou Dianzi University, Hangzhou 310018, China |
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| Abstract: | A new type of fuzzy membership function (FMF) is proposed for interval type-2 fuzzy neural network (IT2FNN) in this paper. Three types of interval type-2 FMF (IT2FMF) can be derived from the proposed type of FMF. And each type of IT2FMF has different shape of footprint of uncertainty (FOU). The derived IT2FMFs are applied to a simplified T2FNN to identify two nonlinear systems. The identification performance of the derived IT2FMFs are compared with Gaussian and ellipsoidal type of IT2FMFs through simulation. Simulation results certify that the derived IT2FMFs can achieve better identification performance than Gaussian and ellipsoidal type of IT2FMFs with elaborately tuning of the parameters for the simplified IT2FNN. |
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