Forecasting Demand for Paddy and Cotton in India: Empirical Analysis Using Machine Learning Models
- Title
- Forecasting Demand for Paddy and Cotton in India: Empirical Analysis Using Machine Learning Models
- Creator
- Jahnavi A.G.; Bashir S.
- Description
- India has a thriving and varied agricultural sector, which has long served as the foundation of the economy. Agriculture contributes significantly to Indias economy and is essential to the nations food security because a sizable percentage of the countrys agricultural population works in farming and associated industries. Indian farmers have managed to successfully produce a variety of commodities, including cash crops like cotton and sugarcane as well as staples like rice and wheat, despite confronting numerous obstacles like small landholdings, poor infrastructure, and unpredictable weather. In this context, it is crucial to examine the status of Indian agriculture at the moment, its advantages and disadvantages, and the possibilities and difficulties confronting farmers and policymakers. 2024 Sachi Nandan Mohanty, Preethi Nanjundan and Tejaswini Kar.
- Source
- Artificial Intelligence in Forecasting: Tools and Techniques, pp. 219-232.
- Date
- 2024-01-01
- Publisher
- CRC Press
- Coverage
- Jahnavi A.G., CHRIST (Deemed to be University), Pune, India; Bashir S., Department of Data Science, CHRIST (Deemed to be University), Pune, India
- Rights
- Restricted Access
- Relation
- ISBN: 978-104005150-4; 978-103250615-9
- Format
- Online
- Language
- English
- Type
- Book chapter
Collection
Citation
Jahnavi A.G.; Bashir S., “Forecasting Demand for Paddy and Cotton in India: Empirical Analysis Using Machine Learning Models,” CHRIST (Deemed To Be University) Institutional Repository, accessed February 23, 2025, https://archives.christuniversity.in/items/show/18062.