基于时空知识图谱的水稻施肥策略推理方法

IF 2.1 3区 地球科学 Q2 GEOGRAPHY
Yiting Lin, Daichao Li, Peng Peng, Jianqin Liang, Fei Ding, Xinlei Jin, Zhan Zeng
{"title":"基于时空知识图谱的水稻施肥策略推理方法","authors":"Yiting Lin, Daichao Li, Peng Peng, Jianqin Liang, Fei Ding, Xinlei Jin, Zhan Zeng","doi":"10.1111/tgis.13166","DOIUrl":null,"url":null,"abstract":"The lack of multidimensional knowledge means that current reasoning methods for rice fertilization cannot make decisions accurate when faced with complex spatiotemporal conditions in general. Therefore, we propose a reasoning method for rice fertilization strategy based on spatiotemporal knowledge graph. First, we systematically organize multisource expert knowledge about rice fertilization, and construct an ontology for rice fertilization consisting of five core elements: rice variety, planting environment, nutrition diagnosis, fertilization schemes, and time and place. Spatiotemporal differences in rice fertilization knowledge are expressed by assessing spatiotemporal concepts, relations, and state instances. Second, we propose a reasoning method for rice fertilization strategy based on the constructed knowledge graph. This method leverages a certainty factor model for nutrition diagnosis and integrates case‐based and rule‐based reasoning to determine fertilization schemes for different stages. Finally, taking Pucheng County, China, as an example, knowledge from crowd‐sensing data is obtained to construct a knowledge graph using the proposed method. The results demonstrate the method can support the expression and complex reasoning of rice fertilization decisions under different spatiotemporal conditions.","PeriodicalId":47842,"journal":{"name":"Transactions in GIS","volume":"208 1","pages":""},"PeriodicalIF":2.1000,"publicationDate":"2024-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A reasoning method for rice fertilization strategy based on spatiotemporal knowledge graph\",\"authors\":\"Yiting Lin, Daichao Li, Peng Peng, Jianqin Liang, Fei Ding, Xinlei Jin, Zhan Zeng\",\"doi\":\"10.1111/tgis.13166\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The lack of multidimensional knowledge means that current reasoning methods for rice fertilization cannot make decisions accurate when faced with complex spatiotemporal conditions in general. Therefore, we propose a reasoning method for rice fertilization strategy based on spatiotemporal knowledge graph. First, we systematically organize multisource expert knowledge about rice fertilization, and construct an ontology for rice fertilization consisting of five core elements: rice variety, planting environment, nutrition diagnosis, fertilization schemes, and time and place. Spatiotemporal differences in rice fertilization knowledge are expressed by assessing spatiotemporal concepts, relations, and state instances. Second, we propose a reasoning method for rice fertilization strategy based on the constructed knowledge graph. This method leverages a certainty factor model for nutrition diagnosis and integrates case‐based and rule‐based reasoning to determine fertilization schemes for different stages. Finally, taking Pucheng County, China, as an example, knowledge from crowd‐sensing data is obtained to construct a knowledge graph using the proposed method. The results demonstrate the method can support the expression and complex reasoning of rice fertilization decisions under different spatiotemporal conditions.\",\"PeriodicalId\":47842,\"journal\":{\"name\":\"Transactions in GIS\",\"volume\":\"208 1\",\"pages\":\"\"},\"PeriodicalIF\":2.1000,\"publicationDate\":\"2024-04-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Transactions in GIS\",\"FirstCategoryId\":\"89\",\"ListUrlMain\":\"https://doi.org/10.1111/tgis.13166\",\"RegionNum\":3,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"GEOGRAPHY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Transactions in GIS","FirstCategoryId":"89","ListUrlMain":"https://doi.org/10.1111/tgis.13166","RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"GEOGRAPHY","Score":null,"Total":0}
引用次数: 0

摘要

由于缺乏多维知识,目前的水稻施肥推理方法在面对复杂的时空条件时无法做出准确的决策。因此,我们提出了一种基于时空知识图谱的水稻施肥策略推理方法。首先,我们对水稻施肥的多源专家知识进行了系统整理,构建了由水稻品种、种植环境、营养诊断、施肥方案和时间地点五个核心要素组成的水稻施肥本体。通过评估时空概念、关系和状态实例来表达水稻施肥知识的时空差异。其次,我们提出了一种基于构建的知识图谱的水稻施肥策略推理方法。该方法利用确定性因子模型进行营养诊断,并将基于案例的推理和基于规则的推理相结合,以确定不同阶段的施肥方案。最后,以中国浦城县为例,利用所提出的方法从人群感知数据中获取知识,构建知识图谱。结果表明,该方法可支持不同时空条件下水稻施肥决策的表达和复杂推理。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A reasoning method for rice fertilization strategy based on spatiotemporal knowledge graph
The lack of multidimensional knowledge means that current reasoning methods for rice fertilization cannot make decisions accurate when faced with complex spatiotemporal conditions in general. Therefore, we propose a reasoning method for rice fertilization strategy based on spatiotemporal knowledge graph. First, we systematically organize multisource expert knowledge about rice fertilization, and construct an ontology for rice fertilization consisting of five core elements: rice variety, planting environment, nutrition diagnosis, fertilization schemes, and time and place. Spatiotemporal differences in rice fertilization knowledge are expressed by assessing spatiotemporal concepts, relations, and state instances. Second, we propose a reasoning method for rice fertilization strategy based on the constructed knowledge graph. This method leverages a certainty factor model for nutrition diagnosis and integrates case‐based and rule‐based reasoning to determine fertilization schemes for different stages. Finally, taking Pucheng County, China, as an example, knowledge from crowd‐sensing data is obtained to construct a knowledge graph using the proposed method. The results demonstrate the method can support the expression and complex reasoning of rice fertilization decisions under different spatiotemporal conditions.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Transactions in GIS
Transactions in GIS GEOGRAPHY-
CiteScore
4.60
自引率
8.30%
发文量
116
期刊介绍: Transactions in GIS is an international journal which provides a forum for high quality, original research articles, review articles, short notes and book reviews that focus on: - practical and theoretical issues influencing the development of GIS - the collection, analysis, modelling, interpretation and display of spatial data within GIS - the connections between GIS and related technologies - new GIS applications which help to solve problems affecting the natural or built environments, or business
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信