Name
Title | ||
|---|---|---|
Data-driven approaches for meteorological time series prediction: A comparative study of the state-of-the-art computational intelligence techniques. |
Abstract | ||
|---|---|---|
•Comparative study of computational intelligence (CI) based meteorological prediction.•Eleven variants of advanced state-of-the-art CI techniques have been studied.•A new hybrid CI technique (SpaFBN) has been proposed.•Comparison has been made with respect to prediction of three meteorological variables.•Empirical study shows superiority of BN based techniques in meteorological prediction. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1016/j.patrec.2017.08.009 | Pattern Recognition Letters |
Keywords | Field | DocType |
Computational intelligence,Data-driven modeling,Bayesian network,Time series prediction,Meteorology | Data mining,Time series,Data-driven,Computational intelligence,Multivariate statistics,Fuzzy logic,Bayesian network,Artificial intelligence,Probabilistic logic,Artificial neural network,Mathematics,Machine learning | Journal |
Volume | Issue | ISSN |
105 | C | 0167-8655 |
Citations | PageRank | References |
1 | 0.43 | 6 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Monidipa Das | 1 | 21 | 9.31 |
| Soumya Kanti Ghosh | 2 | 345 | 39.91 |