Modelling and forecasting cotton production using tuned-support vector regression

被引：2

作者：

Saha, Amit ^{[1
]}

Singh, K. N. ^{[2
]}

Ray, Mrinmoy ^{[2
]}

Rathod, Santosha ^{[3
]}

Choudhury, Sharani ^{[4
]}

机构：

[1] Cent Silk Board, Cent Sericultural Res & Training Inst, Srirampura 570008, Mysuru, India

[2] ICAR Indian Agr Stat Res Inst, New Delhi 110012, India

[3] ICAR Indian Inst Rice Res, Hyderabad 500030, India

[4] ICAR Indian Agr Res Inst, New Delhi 110012, India

来源：

CURRENT SCIENCE | 2021年 / 121卷 / 08期

关键词：

ARIMA; cotton production forecasting; SVR; time series; tuned-SVR; PREDICTION;

D O I：

10.18520/cs/v121/i8/1090-1098

中图分类号：

O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

India is the largest producer of cotton in the world. For proper planning and designing of policies related to cotton, robust forecast of future production is utmost necessary. In this study, an effort has been made to model and forecast the cotton production of India using tuned-support vector regression (Tuned-SVR) model, and the importance of tuning has also been pointed out through this study. The Tuned-SVR performed better in both modelling and forecasting of cotton production compared to auto regressive integrated moving average and classical SVR models.

引用

页码：1090 / 1098

页数：9

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