The week's pick
Random Articles
Reseach Article
A Study of Applications of RBF Network
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 94 - Number 2 |
| Year of Publication: 2014 |
| Authors: Yojna Arora, Abhishek Singhal, Abhay Bansal |
10.5120/16315-5553
|
Yojna Arora, Abhishek Singhal, Abhay Bansal . A Study of Applications of RBF Network. International Journal of Computer Applications. 94, 2 ( May 2014), 17-20. DOI=10.5120/16315-5553
Abstract
Forecasting is a method of making statements about certain event whose actual results have not been observed. It seems to be an easy process but is actually not. It requires a lot of analysis on current and past outcomes in order to give timely and accurate timely forecasted results. Radial Basis Function (RBF) is a method proposed in machine learning for making predictions and forecasting. It has been used in various real time applications such as weather forecasting, load forecasting, forecasting about number of tourist and many such applications. The paper includes a detailed survey on RBF network on the basis of its evolution and applications. It also covers explanation about combination of RBF with other techniques such as Fuzzy, Neural Networkand Genetic Algorithm.
References
- Rich Caruana and Alexandru Niculescu-Mizil, 2006, An Empirical Comparison of Supervised Learning Algorithms, Proceedings of the 23rd International Conference on Machine Learning, Pittsburgh, PA
- Leorrey Marquee, Marcus O' Connor and William Remus,1994,Artificial Neural Network Models for Forecasting and Decision Making, International Journal of Forecasting, Volume 10, Issue 1
- Guang-Bin Huang,P. Saratchandran, and Narasimhan Sundararajan,2005,A Generalized Growing and Pruning RBF(GGAP-RBF) Neural Network for Function Approximation, IEEE transactions on Neural Network, VOL. 16, No. 1
- Cheng-Ming Lee and Chia-Nan Ko,2009, Time series prediction using RBF neural networks with a nonlinear time-varying evolution PSOalgorithm,Journal Neurocomputing,Volume 73,
- Hui Peng, Tohru Ozaki, Valerie Haggan-Ozaki, and Yukihiro Toyoda,2003, A Parameter Optimization Method for Radial Basis Function Type Models, IEEE Transactionon Neyral Netwroks, VOL. 14
- J: K. Sing, D. K. Basu ,M. Nasipuri and M. Kundu, 2003, Improved K-means Algorithm in the Design of RBF Neural Networks, IEEE, VOL 2
- S Chen, C. F. N Cowen and P. M Grant, 1991, Orthogonal Least Squares Learning Algorithm For radial Basis Function Networks", IEEE transactions on Neural Network, VOL 2, No 2
- E. S. Chong, S. Chen, and B. Mulgrew,1996, Gradient Radial Basis Function Networks for Nonlinear and Nonstationary Time Series Prediction, IEEE Transactions on Neural Netwroks, VOL. 7, NO. 1
- V. M. Rivas,J. J. Merelo,P. A. Castillo,M. G. Arenas,J. G. Castellano,2003,Evolving RBF neural networks for time-series forecasting with EvRBF, Elsevier
- Read Zamora, Daniel Racoceanu, amd Noureddine Zerhouni Laboratoire,2003, Recurrent radial basis function network for time-series prediction", Engineering Applications of Artificial Intelligence, Elsevier
- Wei-Zhen Lu,Wen-Jian Wang, Xie-Kang Wang, Sui-Hang Yan, and Joseph C. Lam,2004, Potential assessment of a neural network model with PCA/RBF approach for forecasting pollutant trends in Mong Kok urban air, Hong Kong", Environmental Research
- Ioannis N. Daliakopoulos, Paulin Coulibaly and Ioannis K. Tsanis,2005, "Groundwater level forecasting using artificial neural networks", Journal of Hydrology"
- Yang Zhangang Che Yanbo K. W. Eric Cheng School,2007 Genetic Algorithm-Based RBF Neural Network Load Forecasting Model, IEEE
- George Sideratos and Nikos D. Hatziargyriou,2007,An Advanced Statistical Method for Wind Power Forecasting, IEEE Transactions on Power Systems, VOL. 22, NO. 1
- Lean Yu, Kin Keung Lai and Shouyang Wang,2008, Multistage RBF neural network ensemble learning for exchange rates forecasting", Neurocomputing
- Dr. Taymoor and A. Awchi, 2008, Application of Radial Basis Function Neural Networks for Reference Evapotranspiration Prediction", Al-Rafidain Engineering, Vol. 16 No. 1
- Lin-Tao Lv, Na Ji and Jhu- Long Zhang,2008, A RBF Neural Network Model For Anti-Money Laundering, Proceedings of the 2008 International Conference on Wavelet Analysis and Pattern Recognition, Hong Kong, 30-31
- Tiruvenkadam Santhanam and A. C. Subhajini,2011,An Efficient Weather Forecasting System using Radial Basis Function Neural Network", Journal of Computer Science
- HuaiQiang Zhang and JingBing Li ,2012, Prediction of Tourist Quantity Based on RBF Neural Network", Journal of Computers, VOL. 7, NO. 4.
Index Terms
Keywords