{"title":"灰色预测在农业生产价格中的应用","authors":"Jiajun Zong, Quanyin Zhu","doi":"10.1109/MINES.2012.78","DOIUrl":null,"url":null,"abstract":"In order to get the excellent accuracy for price forecast in the agriculture products market, the Grey Prediction method is utilized to forecast the price of the agriculture products in this paper. Ten agriculture products, which extracted from Agricultural Bank of China at January, 2011 to December 2011, are selected to forecast the price about four weeks and compare the Mean Absolute Percentage Errors (MAPE) by Grey Method (GM) and RBF Neural Network (NN). Experiments demonstrate that the GM(1, 1) is not good for forecasting the agriculture products price and is not stable too. While the RBF NN is better then the GM(1, 1). Experiment results prove that this verdict is meaningful and useful to analyze and to research the price forecast in the agriculture products market.","PeriodicalId":208089,"journal":{"name":"2012 Fourth International Conference on Multimedia Information Networking and Security","volume":"37 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"13","resultStr":"{\"title\":\"Apply Grey Prediction in the Agriculture Production Price\",\"authors\":\"Jiajun Zong, Quanyin Zhu\",\"doi\":\"10.1109/MINES.2012.78\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In order to get the excellent accuracy for price forecast in the agriculture products market, the Grey Prediction method is utilized to forecast the price of the agriculture products in this paper. Ten agriculture products, which extracted from Agricultural Bank of China at January, 2011 to December 2011, are selected to forecast the price about four weeks and compare the Mean Absolute Percentage Errors (MAPE) by Grey Method (GM) and RBF Neural Network (NN). Experiments demonstrate that the GM(1, 1) is not good for forecasting the agriculture products price and is not stable too. While the RBF NN is better then the GM(1, 1). Experiment results prove that this verdict is meaningful and useful to analyze and to research the price forecast in the agriculture products market.\",\"PeriodicalId\":208089,\"journal\":{\"name\":\"2012 Fourth International Conference on Multimedia Information Networking and Security\",\"volume\":\"37 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-11-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"13\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 Fourth International Conference on Multimedia Information Networking and Security\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/MINES.2012.78\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 Fourth International Conference on Multimedia Information Networking and Security","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MINES.2012.78","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Apply Grey Prediction in the Agriculture Production Price
In order to get the excellent accuracy for price forecast in the agriculture products market, the Grey Prediction method is utilized to forecast the price of the agriculture products in this paper. Ten agriculture products, which extracted from Agricultural Bank of China at January, 2011 to December 2011, are selected to forecast the price about four weeks and compare the Mean Absolute Percentage Errors (MAPE) by Grey Method (GM) and RBF Neural Network (NN). Experiments demonstrate that the GM(1, 1) is not good for forecasting the agriculture products price and is not stable too. While the RBF NN is better then the GM(1, 1). Experiment results prove that this verdict is meaningful and useful to analyze and to research the price forecast in the agriculture products market.