Spring rainfall prediction based on remote linkage controlling using adaptive neuro-fuzzy inference system (ANFIS)

Theoretical and Applied Climatology

Volumn 101, Issue 1, 2010, Pages 217-233

  Fallah Ghalhary, Gholam Abbas ^a,b   Habibi Nokhandan, Majid ^b   Mousavi Baygi, Mohammad ^c   Khoshhal, Javad ^a   Barzoki, Akbar Shaemi ^d  

^a UNIVERSITY OF ISFAHAN   (Iran)

^b Climatological Research Institute   (Iran)

^c FERDOWSI UNIVERSITY OF MASHHAD   (Iran)

^d Payam Noor University of Aran   (Iran)

Author keywords

[No Author keywords available]

Indexed keywords

CLIMATE PREDICTION; PRECIPITABLE WATER; RAINFALL; RELATIVE HUMIDITY; SEA LEVEL PRESSURE; SEA SURFACE TEMPERATURE; SPRING (SEASON); SYNOPTIC METEOROLOGY; WATER CONTENT;

IRAN; RAZAVI KHORASAN;

EID: 77953808998     PISSN: 0177798X     EISSN: 14344483     Source Type: Journal    
DOI: 10.1007/s00704-009-0194-x     Document Type: Article

References (17)

1. Abraham A, Sajith N, Joseph B (2001) Will we have a wet summer? Long-term rain forecasting using soft computing models, modelling and simulation. Publication of the Society for Computer Simulation International, Prague, pp 1044-1048.
2. Alijani B (2006) Synoptic climatology, 2nd edn. SAMT, USA, p 258 in Farsi. ISBN 9-609-459-964.
3. Aoyama A, Doyle FJ, Venkatasubramanian V (1995) Control-affine fuzzy neural network approach for nonlinear process control. J Process Control 5: 375-386.
4. Bardossy A, Duckstein L (1995) Fuzzy rule-based modeling with applications to geophysical, biological and engineering sciences. CRC, Boca Raton, p 232.
5. Cavazos T (2000) Using self-organizing maps to investigate extreme climate event: an application to wintertime rainfall in the Balkans. J Climate 13: 1718-1732 ISSN: 1520-0442. Available at http://ams. allenpress. com/perlserv/?request=get-toc& issn=1520-0442& volume=13& issue=10.
6. Choi L (1999) an application hydroinformatic tools for rainfall forecasting. Ph. D. Thesis, University of New South Wales, Australia, 752 pp.
7. Dubois P, Prade H (1980) Fuzzy sets and systems: theory and applications. Academic, San Diego, p 393.
8. Fallah-Ghalhary GA, Mousavi Baygi M, Habibi Nokhandan M (2009) Annual rainfall forecasting by using Mamdani fuzzy inference system. Res J Environ Sci 3(4): 400-413.
9. Halid H, Ridd P (2002) Modeling inter-annual variation of a local rainfall data using a fuzzy logic technique. Proceedings of the International Forum on Climate Prediction, James Cook University, Australia, First Proof, pp 166-170.
10. Haltiner GJ, Williams RT (1980) Numerical prediction and dynamic meteorology, 2nd edn. Wiley, New York, p 447. ISBN 0471059714.
11. Leondes TC (1999) Fuzzy theory system, techniques and applications, vol 2. Academic, New York, p 954.
12. Liu H, Chandrasekhar V (2000) Classification of hydrometeors based on polar metric radar measurements: development of fuzzy logic and neuro-fuzzy systems, and in situ validation. J Atmos Ocean Technol 17: 140-164. doi: 10. 1175/1520-0426.
13. Maria C, Haroldo F, Ferreira N (2005) Artificial neural network technique for rainfall forecasting applied to the Sao Paulo region. J Hydrol 301: 146-162. doi: 10. 1016/j. jhydrol. 2004. 06. 028 Available at http://www. sciencedirect. com/science.
14. Pongracz R, Bartholy J (2006) Regional effects of ENSO in Central/Eastern Europe. ADGEO 6: 133-137 ISSN: 1680-7340. Available at http://www. adv-geosci. net/6/index. html.
15. Suwardi A, Takenori K, Shuhei K (2006) Neuro-fuzzy approaches for modeling the wet season tropical rainfall. Agricultural Information Research 15: 331-341 ISSN: 0916-9482. Available at http://www. jstage. jst. go. jp/article/air/15/3/331/_pdf, doi: 10. 3173/air. 15. 331.
16. Zadeh LA (1965) Fuzzy sets. Inf Control 8: 338-353.
17. Zimmermann HJ (1985) Fuzzy set theory-and its applications. Kluwer-Nijhoff, Boston, p 363.