Application of global SST and SLP data for drought forecasting on Tehran plain using data mining and ANFIS techniques

Theoretical and Applied Climatology

Volumn 104, Issue 1-2, 2011, Pages 71-81

  Farokhnia, Ashkan ^a,b   Morid, Saeed ^a   Byun, Hi Ryong ^c  

^a TARBIAT MODARES UNIVERSITY   (Iran)

^b AEROSPACE RESEARCH INSTITUTE   (Iran)

^c Pukyong National University   (South Korea)

Author keywords

[No Author keywords available]

Indexed keywords

DATA MINING; DATA SET; DROUGHT; FORECASTING METHOD; RISK ASSESSMENT; SEA LEVEL PRESSURE; SEA SURFACE TEMPERATURE;

IRAN; TEHRAN [IRAN];

EID: 79955067051     PISSN: 0177798X     EISSN: 14344483     Source Type: Journal    
DOI: 10.1007/s00704-010-0317-4     Document Type: Article

References (38)

1. Abbaspour KC, Yang J, Maximov I, Siber R, Bogner K, Mieleitner J, Zobrist J, Srinivasan R (2007) Modelling hydrology and water quality in the prealpine/alpine Thur watershed using SWAT. J Hydrol 333: 413-430.
2. Almeira GJ, Scian B (2006) Some atmospheric and oceanic indices as predictors of seasonal rainfall in the Del Plata Basin of Argentina. J Hydrol 329: 350-359.
3. Aqil M, Kita I, Yano A, Nishiyama S (2007) A comparative study of artificial neural networks and neuro-fuzzy in continuous modeling of the daily and hourly behaviour of runoff. J Hydrol 337: 22-34.
4. ASCE Task Committee on Applications of Artificial Neural Networks in Hydrology (2000) Artificial neural networks in hydrology: I: preliminary concepts; II: hydrologic applications. J Hydrol Eng 5: 115-137.
5. Berk RA (2005) Data mining within a regression framework. In: Maimon O, Rokach L (eds) Data mining and knowledge discovery handbook. Springer, New York, pp 231-256.
6. Brown M, Harris C (1994) Neurofuzzy adaptive modeling and control. Prentice Hall, Upper Saddle River.
7. Byun HR, Wilhite DA (1999) Daily quantification of drought severity and duration. J Clim 5: 1181-1201.
8. Chen WS, Du YK (2009) Using neural networks and data mining techniques for the financial distress prediction model. Expert Syst Appl 36: 4057-4086.
9. Chiew FHS, McMahon TA (2002) Global ENSO-streamflow teleconnection, streamflow forecasting and interannual variability. Hydrol Sci J 47: 505-522.
10. Chiu SL (1994) Fuzzy model identification based on cluster estimation. J Intell Fuzzy Syst 2: 267-278.
11. Drosdowsky W, Chambers LE (2001) Near global scale sea surface temperature anomalies as predictors of Australian seasonal rainfall. J Clim 14: 1677-1687.
12. Han J, Kamber M (2006) Data mining: concepts and techniques, 2nd edn. Morgan Kaufmann, San Francisco.
13. Jang JSR (1993) ANFIS: adaptive-network-based fuzzy inference systems. IEEE Trans Syst Man Cybern 23: 665-685.
14. Jang JSR, Sun CT (1995) Neuro-fuzzy modeling and control. Proc IEEE 83: 378-406.
15. Karimi J (2007) Study of moisture sources of Iran's precipitations. Dissertation, Tarbiat Modares University.
16. Leahy P, Kiely G, Corcoran G (2008) Structural optimisation and input selection of an artificial neural network for river level prediction. J Hydrol 355: 192-201.
17. Mamdani EH, Assilian S (1974) An experiment in linguistic synthesis with a fuzzy logic controller. Int J Man Mach Stud 7: 1-13.
18. Marce R, Comerma M, García JC, Armengol J (2004) A neuro-fuzzy modeling tool to estimate fluvial nutrient loads in watersheds under time-varying human impact. Limnol and Oceanogr Method 2: 342-355.
19. Mishra AK, Desaia VR (2006) Drought forecasting using feed-forward recursive neural network. Ecol Model 198: 127-138.
20. Mitra S, Pal SK, Mitra P (2002) Data mining in soft computing framework: a survey. IEEE Trans Neural Netw 13: 3-14.
21. Moreira EE, Coelho CA, Paulo AA, Pereira LS, Mexia JT (2008) SPI-based drought category prediction using loglinear models. J Hydrol 354: 116-130.
22. Morid S, Moghaddasi M, Arshad S, Omid M (2005) Drought Index Package (Version 2). Tarbiat Modarres University, Tehran.
23. Morid S, Smakhtin V, Moghaddasi M (2006) Comparison of seven meteorological indices for drought monitoring in Iran. Int J Climatol 26: 971-985.
24. Morid S, Smakhtin V, Bagherzadeh K (2007) Drought forecasting using artificial neural networks and time series of drought indices. Int J Climatol 27: 2103-2111.
25. Munoz-Diaz FS, Rodrigo FS (2006) Effects of the North Atlantic oscillation on the probability for climatic categories of local monthly rainfall in Southern Spain. Int J Climatol 23: 381-397.
26. Nayak PC, Sudheer KP, Rangan DM, Ramasastrid KS (2004) A neuro-fuzzy computing technique for modeling hydrological time series. J Hydrol 291: 52-66.
27. Noori R, Karbassi AR, Farokhnia A, Dehghani M (2009a) Predicting the longitudinal dispersion coefficient using support vector machine and adaptive neuro-fuzzy inference system techniques. Environ Eng Sci 26: 1503-1510.
28. Noori R, Abdoli MA, Farokhnia A, Abbasi M (2009b) Results uncertainty of solid waste generation forecasting by hybrid of wavelet transform-ANFIS and wavelet transform-neural network. Expert Syst Appl 36: 9991-9999.
29. Noori R, Hoshyaripour G, Ashrafi K, Nadjar-Araabi B (2010) Uncertainty analysis of developed ANN and ANFIS models in prediction of carbon monoxide daily concentration. Atmos Environ 44: 476-482.
30. Ojala T (1995) Neuro-fuzzy systems in control. Dissertation, Tampere University of Technology.
31. Pilon PJ, Condie R, Harvey KD (1985) User manual of Consolidated Frequency Analysis Package 88. Environment Canada, Ottawa.
32. Rumelhart DE, Hinton GE, Williams RJ (1986) Learning representations by back-propagating errors. Nature 323: 533-536.
33. Smakhtin VU, Hughes DA (2007) Automated estimation and analyses of drought characteristics from monthly rainfall data. Environ Model Softw 22: 880-890.
34. Sugeno M, Kang GT (1988) Structure identification of fuzzy model. Fuzzy Sets Syst 28: 15-33.
35. Takagi T, Sugeno M (1983) Derivation of fuzzy control rules from human operator's control actions. In: Proc IFAC Symp Fuzzy Inf, pp 55-60.
36. Tsukamoto Y (1979) An approach to fuzzy reasoning method. In: Gupta MM, Ragade RK, Yager RR (eds) Advances in fuzzy set theory and applications. Elsevier, Amsterdam, pp 137-149.
37. Zadeh LA (1965) Fuzzy sets. Inf Control 8: 338-353.
38. Zealand CM, Burn DH, Simonovic SP (1999) Short term streamflow forecasting using artificial neural network. J Hydrol 214: 32-48.