{"title":"随机模型在印度甘蔗生产中的应用","authors":"R. K. Priya, Kausalya Nataraj","doi":"10.20546/ijcmas.2024.1301.006","DOIUrl":null,"url":null,"abstract":"Forecasting is an essential tool to estimate the future trend of any crop shortly. There are various techniques in the present scenario for predicting future figures and Auto Regressive Integrated Moving Average (ARIMA) is one among them. Sugarcane is an imperative crop in India, keeping in view its importance for many areas of the country and its diverse uses. The present study was intended to check and identify the best forecasting model of sugarcane production in India using historical data between the years 2001 to 2020, based on the estimation of a suitable ARIMA model. The analysis of ACF & PACF of different series revealed that ARIMA was the most suitable model for forecasting based on diagnostics, such as ACF, PACF, and AIC. The selected ARIMA model predicted the sugarcane production for the immediate 10 years from 2021.","PeriodicalId":13777,"journal":{"name":"International Journal of Current Microbiology and Applied Sciences","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Application of Stochastic Model in the Production of Sugarcane in India\",\"authors\":\"R. K. Priya, Kausalya Nataraj\",\"doi\":\"10.20546/ijcmas.2024.1301.006\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Forecasting is an essential tool to estimate the future trend of any crop shortly. There are various techniques in the present scenario for predicting future figures and Auto Regressive Integrated Moving Average (ARIMA) is one among them. Sugarcane is an imperative crop in India, keeping in view its importance for many areas of the country and its diverse uses. The present study was intended to check and identify the best forecasting model of sugarcane production in India using historical data between the years 2001 to 2020, based on the estimation of a suitable ARIMA model. The analysis of ACF & PACF of different series revealed that ARIMA was the most suitable model for forecasting based on diagnostics, such as ACF, PACF, and AIC. The selected ARIMA model predicted the sugarcane production for the immediate 10 years from 2021.\",\"PeriodicalId\":13777,\"journal\":{\"name\":\"International Journal of Current Microbiology and Applied Sciences\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-01-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Current Microbiology and Applied Sciences\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.20546/ijcmas.2024.1301.006\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Current Microbiology and Applied Sciences","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.20546/ijcmas.2024.1301.006","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Application of Stochastic Model in the Production of Sugarcane in India
Forecasting is an essential tool to estimate the future trend of any crop shortly. There are various techniques in the present scenario for predicting future figures and Auto Regressive Integrated Moving Average (ARIMA) is one among them. Sugarcane is an imperative crop in India, keeping in view its importance for many areas of the country and its diverse uses. The present study was intended to check and identify the best forecasting model of sugarcane production in India using historical data between the years 2001 to 2020, based on the estimation of a suitable ARIMA model. The analysis of ACF & PACF of different series revealed that ARIMA was the most suitable model for forecasting based on diagnostics, such as ACF, PACF, and AIC. The selected ARIMA model predicted the sugarcane production for the immediate 10 years from 2021.
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