Robust interval regression analysis using neural networks
Fuzzy Sets and Systems
Geometric particle swarm optimization
Journal of Artificial Evolution and Applications - Particle Swarms: The Second Decade
Learning to play games using a PSO-based competitive learning approach
IEEE Transactions on Evolutionary Computation
An approach to multimodal biomedical image registration utilizing particle swarm optimization
IEEE Transactions on Evolutionary Computation
Comprehensive learning particle swarm optimizer for global optimization of multimodal functions
IEEE Transactions on Evolutionary Computation
Particle Swarm Optimization: Basic Concepts, Variants and Applications in Power Systems
IEEE Transactions on Evolutionary Computation
Function approximation using fuzzy neural networks with robust learning algorithm
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Identification of nonlinear dynamic systems using functional linkartificial neural networks
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Robust radial basis function neural networks
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
On the optimal design of fuzzy neural networks with robust learningfor function approximation
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Nonlinear dynamic system identification using Chebyshev functionallink artificial neural networks
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
A hybrid of genetic algorithm and particle swarm optimization for recurrent network design
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Particle Swarm Optimization With Recombination and Dynamic Linkage Discovery
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Hybrid Particle Swarm Optimization With Wavelet Mutation and Its Industrial Applications
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
OPSO: Orthogonal Particle Swarm Optimization and Its Application to Task Assignment Problems
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Robust TSK fuzzy modeling for function approximation with outliers
IEEE Transactions on Fuzzy Systems
Robust error measure for supervised neural network learning with outliers
IEEE Transactions on Neural Networks
Robust support vector regression networks for function approximation with outliers
IEEE Transactions on Neural Networks
Identification and control of dynamical systems using neural networks
IEEE Transactions on Neural Networks
IEEE Transactions on Neural Networks
Preliminary Study on Wilcoxon Learning Machines
IEEE Transactions on Neural Networks
Analysis and synthesis of feedforward neural networks using discrete affine wavelet transformations
IEEE Transactions on Neural Networks
Recurrent neural networks and robust time series prediction
IEEE Transactions on Neural Networks
Application of the recurrent multilayer perceptron in modeling complex process dynamics
IEEE Transactions on Neural Networks
Memory neuron networks for identification and control of dynamical systems
IEEE Transactions on Neural Networks
A robust backpropagation learning algorithm for function approximation
IEEE Transactions on Neural Networks
IEEE Transactions on Neural Networks
Expert Systems with Applications: An International Journal
| Hi-index | 12.05 |
The paper introduces a novel method of adaptive robust identification of complex nonlinear dynamic plants including Box Jenkin, Mackey Glass and Sunspot series under the presence of strong outliers in the training samples. The identification model consists of a low complexity single layer functional link artificial neural network (FLANN) in the feed forward path and another on the feedback path. The connecting weights are iteratively adjusted by a population based particle swarm optimization technique so that a robust cost function (RCF) of the model-error is minimized. To demonstrate robust identification performance up to 50% random samples of the plant output is contaminated with strong outliers and are employed for training the model using PSO tool. Identification of wide varieties of benchmark complex static and dynamic plants is carried out through simulation study and the performance obtained are compared with those obtained from using standard squared error norm as CF. It is in general observed that, the Wilcoxon norm provides best identification performance compared to squared error and other RCFs based models.