All Outputs (25)

Support Vector Regression for Multi-objective Parameter Estimation of Interval Type-2 Fuzzy Systems (2020)
Book Chapter

© 2020, Springer Nature Singapore Pte Ltd. This paper presents a support vector regression-based multi-objective parameter estimation method for interval type-2 fuzzy systems, which deals with prediction interval rather than its crisp output value. S... Read More about Support Vector Regression for Multi-objective Parameter Estimation of Interval Type-2 Fuzzy Systems.

Recurrent Interval Type-2 Fuzzy Wavelet Neural Network with Stable Learning Algorithm: Application to Model-Based Predictive Control (2020)
Journal Article

Fuzzy neural networks, with suitable learning strategy, have been demonstrated as an effective tool for online data modeling. However, it is a challenging task to construct a model to ensure its quality and stability for non-stationary dynamic system... Read More about Recurrent Interval Type-2 Fuzzy Wavelet Neural Network with Stable Learning Algorithm: Application to Model-Based Predictive Control.

A novel non-iterative parameter estimation method for interval type-2 fuzzy neural networks based on a dynamic cost function (2019)
Conference Proceeding

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)
Conference Proceeding

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)
Conference Proceeding

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.