SEASONAL RAINFALL PREDICTION BASED ON SYNOPTICALLY PATTERNS BY USING ADAPTIVE NEURO-FUZZY INFERENCE SYSTEM (ANFIS)

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FALAH GHALHARI GH.A.; MOUSAVI BAYEGI S.M.; HABIBI NOUKHANDAN M.

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Journal: Physical Geography Research Year:2009 | Volume:- | Issue:66 Page(s): 121-139

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Title

SEASONAL RAINFALL PREDICTION BASED ON SYNOPTICALLY PATTERNS BY USING ADAPTIVE NEURO-FUZZY INFERENCE SYSTEM (ANFIS)

Author(s)

FALAH GHALHARI GH.A. | MOUSAVI BAYEGI S.M. | HABIBI NOUKHANDAN M. | Issue Writer Certificate

Keywords

RAINFALL PREDICTIONQ3

SYNOPTICALLY PATTERNSQ2

ADAPTIVE NEURO-FUZZY INFERENCE SYSTEM (ANFIS)Q3

Abstract

Weather process prediction is the tool for managers to planning the future political for maximum operation. The aim of this research is relation investigation of large scale SYNOPTICALLY PATTERNS with Seasonal rainfall of Khorasan province. In this research, we have analyzed 37 years of rainfall data in khorasan province that is located the northeastern part of Iran .We attempted to train Adaptive Neuro-Fuzzy Inference System (ANFIS) based on SYNOPTICALLY PATTERNS with 37 years of rainfall data. For performance evaluation, ANFIS predicted outputs were compared with the actual rainfall data. In This Study, at the first step, the relationships between synoptically pattern variations including Sea Level Pressure (SLP), Sea Surface Temperature (SST), Sea Surface Pressure Difference (DSLP), Sea Surface Temperature Difference (DSST), Air Temperature at 850 hpa, geopotential high at 500 hpa level, Relative Humidity at 300 hpa are investigated. in the second step, model was calibrated from 1970 to 1992.Finally, RAINFALL PREDICTION is performed from 1993 to 2002. Simulation results reveal that Adaptive Neuro-Fuzzy Inference System (ANFIS) is promising and efficient.

Cites

ANALYSIS THE RELATION OF SYNOPTIC PATTERNS WITH DAILY HEAVY PRECIPITATION IN GUILAN PROVINCE DURING SEPTEMBER (1976- 2005)

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APA: Copy

FALAH GHALHARI, GH.A., MOUSAVI BAYEGI, S.M., & HABIBI NOUKHANDAN, M.. (2009). SEASONAL RAINFALL PREDICTION BASED ON SYNOPTICALLY PATTERNS BY USING ADAPTIVE NEURO-FUZZY INFERENCE SYSTEM (ANFIS). PHYSICAL GEOGRAPHY RESEARCH QUARTERLY, -(66), 121-139. SID. https://sid.ir/paper/138775/en

Vancouver: Copy

FALAH GHALHARI GH.A., MOUSAVI BAYEGI S.M., HABIBI NOUKHANDAN M.. SEASONAL RAINFALL PREDICTION BASED ON SYNOPTICALLY PATTERNS BY USING ADAPTIVE NEURO-FUZZY INFERENCE SYSTEM (ANFIS). PHYSICAL GEOGRAPHY RESEARCH QUARTERLY[Internet]. 2009;-(66):121-139. Available from: https://sid.ir/paper/138775/en

IEEE: Copy

GH.A. FALAH GHALHARI, S.M. MOUSAVI BAYEGI, and M. HABIBI NOUKHANDAN, “SEASONAL RAINFALL PREDICTION BASED ON SYNOPTICALLY PATTERNS BY USING ADAPTIVE NEURO-FUZZY INFERENCE SYSTEM (ANFIS),” PHYSICAL GEOGRAPHY RESEARCH QUARTERLY, vol. -, no. 66, pp. 121–139, 2009, [Online]. Available: https://sid.ir/paper/138775/en

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