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  • 标题:Hybrid Statistical Models for Forecasting Yield of Mango and Banana in Tamil Nadu, India
  • 本地全文:下载
  • 作者:P.Sujatha
  • 期刊名称:Asian Journal of Agricultural Extension, Economics & Sociology
  • 电子版ISSN:2320-7027
  • 出版年度:2021
  • 卷号:39
  • 期号:11
  • 页码:168-174
  • DOI:10.9734/ajaees/2021/v39i1130738
  • 语种:English
  • 出版社:Sciencedomain International
  • 摘要:Horticulture sector plays a prominent role in economic growth of India. India is the second largest producer of fruits and vegetables in the world next to China. Among the horticultural crops, fruit crops are cultivated in majority of the area in India. Fruit crops play a significant role in the economic development, nutritional security, employment generation, and total growth of country. India is major producer of mango and banana, among fruit crops. The objective of this research paper is to predicate the yield of mango and banana in Tamil Nadu using different models such as linear and nonlinear, parametric, and non-parametric statistical models. In this research, a hybrid model had been proposed, which consists of linear and nonlinear models. In this hybrid model, combination of the Autoregressive Integrated Moving Average (ARIMA) and Regression model were used. The present study was conducted in Tamil Nadu. Since, area and production of Mango and Banana are higher in Tamil Nadu. Based on results obtained production and yield of Mango and Banana were predicted for next four years.
  • 关键词:ARIMA;regression model;hybrid model;time series
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