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

共 50 条

[41] Support vector regression with modified firefly algorithm for stock price forecasting
Zhang, Jun
Teng, Yu-Fan
Chen, Wei
APPLIED INTELLIGENCE, 2019, 49 (05) : 1658 - 1674
[42] Forecasting respiratory motion with accurate online support vector regression (SVRpred)
Ernst, Floris
Schweikard, Achim
INTERNATIONAL JOURNAL OF COMPUTER ASSISTED RADIOLOGY AND SURGERY, 2009, 4 (05) : 439 - 447
[43] Forecasting systems reliability based on support vector regression with genetic algorithms
Chen, Kuan-Yu
RELIABILITY ENGINEERING & SYSTEM SAFETY, 2007, 92 (04) : 423 - 432
[44] Forecasting respiratory motion with accurate online support vector regression (SVRpred)
Floris Ernst
Achim Schweikard
International Journal of Computer Assisted Radiology and Surgery, 2009, 4 : 439 - 447
[45] Maximum Power Point Tracking for a PV System Using Tuned Support Vector Regression by Particle Swarm Optimization
Abo-Khalil, Ahmed G.
JOURNAL OF ENGINEERING RESEARCH, 2020, 8 (04): : 139 - 152
[46] Electric Load Forecasting Based on Locally Weighted Support Vector Regression
Elattar, Ehab E.
Goulermas, John
Wu, Q. H.
IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART C-APPLICATIONS AND REVIEWS, 2010, 40 (04): : 438 - 447
[47] Combined forecasting approach for product quality based on support vector regression and gray forecasting model
Lian, Xiaozhen
Liu, Ying
Bu, Xiangjian
Hou, Liang
ADVANCED ENGINEERING INFORMATICS, 2023, 57
[48] Reliability prediction using support vector regression
Fuqing, Yuan
Kumar, Uday
Galar, Diego
INTERNATIONAL JOURNAL OF SYSTEM ASSURANCE ENGINEERING AND MANAGEMENT, 2010, 1 (03) : 263 - 268
[49] Reliability prediction using support vector regression
Yuan Fuqing
Uday Kumar
Diego Galar
International Journal of System Assurance Engineering and Management, 2010, 1 (3)
[50] Short-term wind speed forecasting using variational mode decomposition and support vector regression
Wang, Xiaodan
Yu, Qibing
Yang, Yi
JOURNAL OF INTELLIGENT & FUZZY SYSTEMS, 2018, 34 (06) : 3811 - 3820

← 1 2 3 4 5 →