Feed forward Artificial Neural Network model to predict the average summer-monsoon rainfall in India

被引:69
作者
Chattopadhyay, Surajit [1 ]
机构
[1] Pailan Coll Management & Technol, Kolkata, India
关键词
summer-monsoon rainfall; prediction of monsoon rainfall; Artificial Neural Network model; Multiple Linear Regression forecast;
D O I
10.2478/s11600-007-0020-8
中图分类号
P3 [地球物理学]; P59 [地球化学];
学科分类号
0708 ; 070902 ;
摘要
In the present research, possibility of predicting average summer-monsoon rainfall over India has been analyzed through Artificial Neural Network model. In formulating the ANN - based predictive model, three-layer network has been constructed with sigmoid non-linearity. The monthly summer monsoon rainfall totals, tropical rainfall indices and sea surface temperature anomalies have been considered as predictors while generating the input matrix for the ANN. The data pertaining to the years 1950-1995 have been explored to develop the predictive model. Finally, the prediction performance of neural net has been compared with persistence forecast and Multiple Linear Regression forecast and the supremacy of the ANN has been established over the other processes.
引用
收藏
页码:369 / 382
页数:14
相关论文
共 58 条
[1]  
[Anonymous], 1999, NEURO FUZZY PATTERN
[2]   ON THE ECONOMIC VALUE OF WEATHER FORECASTS IN WILDFIRE SUPPRESSION MOBILIZATION DECISIONS [J].
BROWN, BG ;
MURPHY, AH .
CANADIAN JOURNAL OF FOREST RESEARCH-REVUE CANADIENNE DE RECHERCHE FORESTIERE, 1988, 18 (12) :1641-1649
[3]   SURFACE OZONE IN ATHENS, GREECE, AT THE BEGINNING AND AT THE END OF THE 20TH-CENTURY [J].
CARTALIS, C ;
VAROTSOS, C .
ATMOSPHERIC ENVIRONMENT, 1994, 28 (01) :3-8
[4]   MODELING DAILY PRECIPITATION OCCURRENCE PROCESS WITH MARKOV-CHAIN [J].
CHIN, EH .
WATER RESOURCES RESEARCH, 1977, 13 (06) :949-956
[5]  
Clark CO, 2000, J CLIMATE, V13, P2503, DOI 10.1175/1520-0442(2000)013<2503:IOSAIS>2.0.CO
[6]  
2
[7]  
ELSNER JB, 1992, B AM METEOROL SOC, V73, P49, DOI 10.1175/1520-0477(1992)073<0049:NPCAN>2.0.CO
[8]  
2
[9]  
FERRANTI L, 1990, J ATMOS SCI, V47, P2177, DOI 10.1175/1520-0469(1990)047<2177:TEIAWT>2.0.CO
[10]  
2