{"title":"印度拉贾斯坦邦Kota地区大蒜价格预测模型的比较分析","authors":"Surjeet Singh Dhaka, None Urmila, Dharavath Poolsingh","doi":"10.36956/rwae.v4i4.915","DOIUrl":null,"url":null,"abstract":"Garlic is a well-known spice in India, and Rajasthan is the country's second-largest producer of garlic after Madhya Pradesh. Accurate price predictions are crucial for agricultural commodities, as they significantly impact the accessibility of food for consumers and the livelihoods of farmers, governments, and agribusiness industries. Governments also use these forecasts to support the agricultural sector and ensure food security. A study was conducted in Rajasthan's Kota district to analyze the wholesale price of garlic using data from July 2021 to July 2023 from the Kota fruit and vegetable market. The study used simple moving average (SMA), simple exponential smoothing (SES), and autoregressive integrated moving average (ARIMA) models to forecast garlic prices. The models were validated through mean absolute deviation (MAD), mean squared error (MSE), mean absolute percentage error (MAPE), root mean squared error (RMSE), correlation coefficient (r), and coefficient of variation (CV). The research was conducted utilizing Microsoft Excel and R Studio version 4.2.2 for Windows, and the results showed that the ARIMA (1,0,0) with a non-zero mean model had a strong correlation coefficient (r = 0.91**) and accurately predicted the variation in garlic prices. Based on the analysis, it is recommended to use this model for forecasting and making informed decisions.","PeriodicalId":222396,"journal":{"name":"Research on World Agricultural Economy","volume":"39 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Comparative Analysis of Price Forecasting Models for Garlic (Allium sativum L.) in Kota District of Rajasthan, India\",\"authors\":\"Surjeet Singh Dhaka, None Urmila, Dharavath Poolsingh\",\"doi\":\"10.36956/rwae.v4i4.915\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Garlic is a well-known spice in India, and Rajasthan is the country's second-largest producer of garlic after Madhya Pradesh. Accurate price predictions are crucial for agricultural commodities, as they significantly impact the accessibility of food for consumers and the livelihoods of farmers, governments, and agribusiness industries. Governments also use these forecasts to support the agricultural sector and ensure food security. A study was conducted in Rajasthan's Kota district to analyze the wholesale price of garlic using data from July 2021 to July 2023 from the Kota fruit and vegetable market. The study used simple moving average (SMA), simple exponential smoothing (SES), and autoregressive integrated moving average (ARIMA) models to forecast garlic prices. The models were validated through mean absolute deviation (MAD), mean squared error (MSE), mean absolute percentage error (MAPE), root mean squared error (RMSE), correlation coefficient (r), and coefficient of variation (CV). The research was conducted utilizing Microsoft Excel and R Studio version 4.2.2 for Windows, and the results showed that the ARIMA (1,0,0) with a non-zero mean model had a strong correlation coefficient (r = 0.91**) and accurately predicted the variation in garlic prices. Based on the analysis, it is recommended to use this model for forecasting and making informed decisions.\",\"PeriodicalId\":222396,\"journal\":{\"name\":\"Research on World Agricultural Economy\",\"volume\":\"39 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-10-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Research on World Agricultural Economy\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.36956/rwae.v4i4.915\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Research on World Agricultural Economy","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.36956/rwae.v4i4.915","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
摘要
大蒜在印度是一种著名的香料,拉贾斯坦邦是印度第二大大蒜生产国,仅次于中央邦。准确的价格预测对农产品至关重要,因为这将对消费者获得粮食以及农民、政府和农业综合企业的生计产生重大影响。各国政府还利用这些预测来支持农业部门和确保粮食安全。在拉贾斯坦邦的哥打地区进行了一项研究,利用2021年7月至2023年7月哥打水果和蔬菜市场的数据分析了大蒜的批发价格。采用简单移动平均(SMA)、简单指数平滑(SES)和自回归综合移动平均(ARIMA)模型对大蒜价格进行预测。通过平均绝对偏差(MAD)、均方误差(MSE)、平均绝对百分比误差(MAPE)、均方根误差(RMSE)、相关系数(r)和变异系数(CV)对模型进行验证。利用Microsoft Excel和Windows版本的R Studio 4.2.2进行研究,结果表明,采用非零均值模型的ARIMA(1,0,0)具有较强的相关系数(R = 0.91**),能够准确预测大蒜价格的变化。根据分析,建议使用该模型进行预测和做出明智的决策。
Comparative Analysis of Price Forecasting Models for Garlic (Allium sativum L.) in Kota District of Rajasthan, India
Garlic is a well-known spice in India, and Rajasthan is the country's second-largest producer of garlic after Madhya Pradesh. Accurate price predictions are crucial for agricultural commodities, as they significantly impact the accessibility of food for consumers and the livelihoods of farmers, governments, and agribusiness industries. Governments also use these forecasts to support the agricultural sector and ensure food security. A study was conducted in Rajasthan's Kota district to analyze the wholesale price of garlic using data from July 2021 to July 2023 from the Kota fruit and vegetable market. The study used simple moving average (SMA), simple exponential smoothing (SES), and autoregressive integrated moving average (ARIMA) models to forecast garlic prices. The models were validated through mean absolute deviation (MAD), mean squared error (MSE), mean absolute percentage error (MAPE), root mean squared error (RMSE), correlation coefficient (r), and coefficient of variation (CV). The research was conducted utilizing Microsoft Excel and R Studio version 4.2.2 for Windows, and the results showed that the ARIMA (1,0,0) with a non-zero mean model had a strong correlation coefficient (r = 0.91**) and accurately predicted the variation in garlic prices. Based on the analysis, it is recommended to use this model for forecasting and making informed decisions.