气候变化领域集成服务门户(CCPortal): Machine learning algorithms for predicting rainfall in India

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DOI	10.18520/cs/v126/i3/360-367
	Machine learning algorithms for predicting rainfall in India
	Garai, Sandi; Paul, Ranjit Kumar; Yeasin, Md.; Roy, H. S.; Paul, A. K.
发表日期	2024
ISSN	0011-3891
起始页码	126
结束页码	3
卷号	126 期号:3
英文摘要	Due to the changing climate and frequent occurrence of extreme events, farmers face significant challenges. Precise rainfall prediction is necessary for proper crop planning. The presence of nonlinearity and chaotic structure in the historical rainfall series distorts the performances of the usual prediction models. In the present study, algorithms based on complete ensemble empirical mode decomposition with adaptive noise combined with stochastic models like autoregressive integrated moving average and generalized autoregressive conditional heteroscedasticity; machine learning techniques like random forest, artificial neural network, support vector regression and kernel ridge regression (KRR) have been proposed for predicting rainfall series. KRR has been considered to combine predicted intrinsic mode functions and residuals generated by various algorithms to capture the volatility in the series. The proposed algorithms have been applied for predicting rainfall in three selected subdivisions of India, namely, Assam and Meghalaya, Konkan and Goa, and Punjab. An empirical comparison of the proposed algorithms with the existing models revealed that the developed models have outperformed the latter.
英文关键词	Climate change; crop planning; empirical comparison; machine learning; prediction; rainfall
语种	英语
WOS研究方向	Science & Technology - Other Topics
WOS类目	Multidisciplinary Sciences
WOS记录号	WOS:001195542400004
来源期刊	CURRENT SCIENCE
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/292705
作者单位	Indian Council of Agricultural Research (ICAR); ICAR - Indian Agricultural Research Institute; Indian Council of Agricultural Research (ICAR); ICAR - Indian Institute of Agricultural Biotechnology; Indian Council of Agricultural Research (ICAR); ICAR - Indian Agricultural Statistics Research Institute
推荐引用方式 GB/T 7714	Garai, Sandi,Paul, Ranjit Kumar,Yeasin, Md.,et al. Machine learning algorithms for predicting rainfall in India[J],2024,126(3).
APA	Garai, Sandi,Paul, Ranjit Kumar,Yeasin, Md.,Roy, H. S.,&Paul, A. K..(2024).Machine learning algorithms for predicting rainfall in India.CURRENT SCIENCE,126(3).
MLA	Garai, Sandi,et al."Machine learning algorithms for predicting rainfall in India".CURRENT SCIENCE 126.3(2024).