Zhuang Jiayu, Xu Shiwei, Li Zhemin, Chen Wei, Wang Dongjie
{"title":"智能信息融合技术在农业监测预警研究中的应用","authors":"Zhuang Jiayu, Xu Shiwei, Li Zhemin, Chen Wei, Wang Dongjie","doi":"10.1109/ICCAR.2015.7166013","DOIUrl":null,"url":null,"abstract":"This paper introduces a dynamic feedback crop simulation system used to simulate and forecast the growth of crops. It was known that a precise and effective crop simulation was beneficial for the investigating of crops' growth and production forecast. The real-time monitoring data applied for this simulation system was derived from Agriculture monitoring and early-warning research space (AMERS) which was established by Agriculture Information Institute of Chinese Academy of Agricultural Sciences. A more accurate and valid simulation system is proposed in this paper, by improving the system of agriculture model with the collected data. The corrected model is able to predict the crop's growth and yields more accurately. During the lifecycle of the whole crops the model is corrected and predicted continuously until the simulated data is highly consistent with the real data. The collected data can be used as the input of the simulation, and the corrected model for real-time feedback. A growth index which was calculated by the monitoring data used to measure the growth of crops was proposed. This growth index will responded to the crops simulation model for system amendment. The result of late growth and yield forecasting will be updated by the revised model. Two applications of this system were briefly introduced.","PeriodicalId":422587,"journal":{"name":"2015 International Conference on Control, Automation and Robotics","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"17","resultStr":"{\"title\":\"Application of intelligence information fusion technology in agriculture monitoring and early-warning research\",\"authors\":\"Zhuang Jiayu, Xu Shiwei, Li Zhemin, Chen Wei, Wang Dongjie\",\"doi\":\"10.1109/ICCAR.2015.7166013\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper introduces a dynamic feedback crop simulation system used to simulate and forecast the growth of crops. It was known that a precise and effective crop simulation was beneficial for the investigating of crops' growth and production forecast. The real-time monitoring data applied for this simulation system was derived from Agriculture monitoring and early-warning research space (AMERS) which was established by Agriculture Information Institute of Chinese Academy of Agricultural Sciences. A more accurate and valid simulation system is proposed in this paper, by improving the system of agriculture model with the collected data. The corrected model is able to predict the crop's growth and yields more accurately. During the lifecycle of the whole crops the model is corrected and predicted continuously until the simulated data is highly consistent with the real data. The collected data can be used as the input of the simulation, and the corrected model for real-time feedback. A growth index which was calculated by the monitoring data used to measure the growth of crops was proposed. This growth index will responded to the crops simulation model for system amendment. The result of late growth and yield forecasting will be updated by the revised model. Two applications of this system were briefly introduced.\",\"PeriodicalId\":422587,\"journal\":{\"name\":\"2015 International Conference on Control, Automation and Robotics\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-05-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"17\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 International Conference on Control, Automation and Robotics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCAR.2015.7166013\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 International Conference on Control, Automation and Robotics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCAR.2015.7166013","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Application of intelligence information fusion technology in agriculture monitoring and early-warning research
This paper introduces a dynamic feedback crop simulation system used to simulate and forecast the growth of crops. It was known that a precise and effective crop simulation was beneficial for the investigating of crops' growth and production forecast. The real-time monitoring data applied for this simulation system was derived from Agriculture monitoring and early-warning research space (AMERS) which was established by Agriculture Information Institute of Chinese Academy of Agricultural Sciences. A more accurate and valid simulation system is proposed in this paper, by improving the system of agriculture model with the collected data. The corrected model is able to predict the crop's growth and yields more accurately. During the lifecycle of the whole crops the model is corrected and predicted continuously until the simulated data is highly consistent with the real data. The collected data can be used as the input of the simulation, and the corrected model for real-time feedback. A growth index which was calculated by the monitoring data used to measure the growth of crops was proposed. This growth index will responded to the crops simulation model for system amendment. The result of late growth and yield forecasting will be updated by the revised model. Two applications of this system were briefly introduced.