1 |
J. H. Seo and Y. H. Kim, "Genetic feature selection for very short-term heavy rainfall prediction," In Proceedings of International Conference on Convergence and Hybrid Information Technology - Lecture Notes in Computer Science 7425, pp. 312-2322, 2012.
|
2 |
J. LEE, J. Kim, J.H. Lee, "Parameter Evaluation to Classify Heavy Rain using SVMs," ISIS, 2011.
|
3 |
L. Ingsrisawang, S, Ingsriswang, S. Somchit, P. Aungsuratana, and W. Khantiyanan, "Machine learning techniques for short-term rain forecasting system in the northeastern part of Thailand", In Proceedings of World Academy of Science, Engineering and Technology, 31, 248-253. 2008.
|
4 |
W. C. Hong, "Rainfall forecasting by technological machine learning models." Appl Math Comput, 200(1), 41-57. 2008.
DOI
ScienceOn
|
5 |
E. Toth, A. Brath, and A. Montanari, "Comparison of short-term rainfall prediction models for real-time flood forecasting." Journal of Hydrology, 29, 132-147. 2000.
|
6 |
A. Staiano. J. Tagliaferri, W. Pedrycz, "Improving RBF networks performance in regression tasks by means of a supervised fuzzy clustering Automatic structure and parameter", Neurocomputing, Vol. 69, pp. 1570-1581, 2006.
DOI
ScienceOn
|
7 |
J. Kennedy and R. Everhart, "Particle Swarm Optimization," Proc. of IEEE International Conference on Neural Networks," Vol. 4, pp. 1942-1948, 1995.
|
8 |
K. E. Parsopoulos and M. N. Vrahatis, "On the Computation of All Global Minimizer Through Particle Swarm Optimization," IEEE Trans. Evolutionary Compuation Vol. 8, No. 3, pp. 211-224, 2004.
DOI
ScienceOn
|
9 |
Korea Meteorological Administration, http://www.kma.go.kr
|
10 |
J. H. Seo and Y. H. Kim, "A survey on rainfall forecast algorithms based on machine learning technique", In Proceedings of KIIS Fall Conference, vol. 21, no 2, pp. 218-l221, 2011.
|
11 |
Y.-H. Kim, W. Kim, K. Min, and Y. Yoon. "Probabilistic context prediction using time-inferred multiple pattern networks", Annual ACM Symposium on Applied Computing, pp. 1015-1019. 2010.
|
12 |
Hsieh, W. W. "Nonlinear principal component analysis by neural networks." Tellus, 53A, 599-15. 2001
|
13 |
S. K. Oh, W. D. Kim, W. Pedrycz, and B. J. Park, "Polynomial-based Radial Basis Function Neural Networks (P-RBF NNs) Realized with the Aid of Particle Swarm Optimization," Fuzzy Sets and Systems, Vol. 163, No. 1, pp. 54-77, 2011.
DOI
ScienceOn
|
14 |
W. Shen, X. Guo, C. Wu, D. Wu, Forecasting stock indices using radial basis function neural networks optimized by artificial fish swarm algorithm, Knowledge-Based Syst. 24 (3) 378-85. 2011.
DOI
ScienceOn
|