Adaptive pattern recognition and neural networks
Adaptive pattern recognition and neural networks
Approximation capabilities of multilayer feedforward networks
Neural Networks
Neural Networks: A Comprehensive Foundation
Neural Networks: A Comprehensive Foundation
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Parameter Selection in Particle Swarm Optimization
EP '98 Proceedings of the 7th International Conference on Evolutionary Programming VII
Feature Selection for Neural Networks through Functional Links Found by Evolutionary Computation
IDA '97 Proceedings of the Second International Symposium on Advances in Intelligent Data Analysis, Reasoning about Data
A Study of Global Optimization Using Particle Swarms
Journal of Global Optimization
Modified high-order neural network for invariant pattern recognition
Pattern Recognition Letters
On-line system identification of complex systems using Chebyshev neural networks
Applied Soft Computing
Information Sciences: an International Journal
A functional-link-neural network for short-term electric load forecasting
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
Predictive models for the breeder genetic algorithm i. continuous parameter optimization
Evolutionary Computation
Genetic Feature Selection for Optimal Functional Link Artificial Neural Network in Classification
IDEAL '08 Proceedings of the 9th International Conference on Intelligent Data Engineering and Automated Learning
Evolution of functional link networks
IEEE Transactions on Evolutionary Computation
The particle swarm - explosion, stability, and convergence in amultidimensional complex space
IEEE Transactions on Evolutionary Computation
Self-organizing hierarchical particle swarm optimizer with time-varying acceleration coefficients
IEEE Transactions on Evolutionary Computation
Identification of nonlinear dynamic systems using functional linkartificial neural networks
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
Planning with a functional neural network architecture
IEEE Transactions on Neural Networks
Nonlinear Knowledge-Based Classification
IEEE Transactions on Neural Networks
International Journal of Data Analysis Techniques and Strategies
| Hi-index | 0.00 |
A hybrid learning scheme (ePSO-BP) to train Chebyshev Functional Link Neural Network (CFLNN) for classification is presented. The proposed method is referred as hybrid CFLNN (HCFLNN). The HCFLNN is a type of feed-forward neural networks which have the ability to transform the nonlinear input space into higher dimensional-space where linear separability is possible. Moreover, the proposed HCFLNN combines the best attribute of particle swarm optimization (PSO), back propagation learning (BP learning), and functional link neural networks (FLNNs). The proposed method eliminates the need of hidden layer by expanding the input patterns using Chebyshev orthogonal polynomials. We have shown its effectiveness of classifying the unknown pattern using the publicly available datasets obtained from UCI repository. The computational results are then compared with functional link neural network (FLNN) with a generic basis functions, PSO-based FLNN, and EFLN. From the comparative study, we observed that the performance of the HCFLNN outperforms FLNN, PSO-based FLNN, and EFLN in terms of classification accuracy.