Modelling and forecasting cotton production using tuned-support vector regression
KRISHI: Publication and Data Inventory Repository
View Archive InfoField | Value | |
Title |
Modelling and forecasting cotton production using tuned-support vector regression
Not Available |
|
Creator |
Amit Saha
K. N. Singh Mrinmoy Ray Santosha Rathod Sharani Choudhury |
|
Subject |
ARIMA
cotton production forecasting SVR time series tuned-SVR |
|
Description |
Not Available
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. Not Available |
|
Date |
2022-02-07T08:48:36Z
2022-02-07T08:48:36Z 2021-10-25 |
|
Type |
Article
|
|
Identifier |
Saha, A., Singh, K. N., Ray, M., Rathod, S. and Choudhury, S. (2021). Modelling and forecasting cotton production using tuned-support vector regression. Current Science, 121(8), 1090-1098.
Not Available http://krishi.icar.gov.in/jspui/handle/123456789/69608 |
|
Language |
English
|
|
Relation |
Not Available;
|
|
Publisher |
Current Science Association in collaboration with the Indian Academy of Sciences
|
|