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A novel non-iterative parameter estimation method for interval type-2 fuzzy neural networks based on a dynamic cost function (2019)
Presentation / Conference Contribution
Khanesar, M. A., Hassan, S., Cambria, E., & Kayacan, E. (2019, June). A novel non-iterative parameter estimation method for interval type-2 fuzzy neural networks based on a dynamic cost function. Presented at International Conference on Fuzzy Systems (FUZZ -IEEE 2019), New Orleans, Louisiana, USA

Non-iterative methods for parameter estimation for interval type-2 neuro-fuzzy structure are fast to implement, when compared to online methods, and need no –or a few– parameters to be tuned. In this paper, a novel dynamic cost function, which define... Read More about A novel non-iterative parameter estimation method for interval type-2 fuzzy neural networks based on a dynamic cost function.

Ensemble of Deep Belief Network and Bayesian Adaptive Aggregation for Regression (2019)
Presentation / Conference Contribution
Hassan, S., Khanesari, M. A., Jan, M. T., & Khan Mashwani, W. (2019, March). Ensemble of Deep Belief Network and Bayesian Adaptive Aggregation for Regression. Presented at 2019 International Conference on Information Science and Communication Technology (ICISCT), Karachi, Pakistan

Ensemble modeling of Neural Networks is a strategy where multiple alternative models (ensemble members) are constructed and then their forecasts are ensembled using various combination approaches. Ensemble of Neural Networks has proved the concept be... Read More about Ensemble of Deep Belief Network and Bayesian Adaptive Aggregation for Regression.

Nonlinear System Identification Using Type-2 Fuzzy Recurrent Wavelet Neural Network (2019)
Presentation / Conference Contribution
Tafti, B. E. F., Khanesar, M. A., & Teshnehlab, M. (2019, January). Nonlinear System Identification Using Type-2 Fuzzy Recurrent Wavelet Neural Network. Presented at 2019 7th Iranian Joint Congress on Fuzzy and Intelligent Systems (CFIS), Bojnord, Iran

In this paper, the integration of Type-2 fuzzy set theory and recurrent wavelet neural network(WNN) is proposed to allow managing of non-uniform uncertainties for identifying non-linear dynamic system. The proposed Type-2 fuzzy WNN is inherently a re... Read More about Nonlinear System Identification Using Type-2 Fuzzy Recurrent Wavelet Neural Network.