Prediction Model for Soybean Productivity
This paper presents a holistic approach to biological and agricultural research focused on the use of interconnected technologies in the context of climate change. Researchers from different countries have analyzed how smart technologies can help agriculture adapt to these changes. The most represen...
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| Format: | Article |
| Language: | English |
| Published: |
Bucharest University of Economic Studies
2024-05-01
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| Series: | Database Systems Journal |
| Subjects: | |
| Online Access: | https://www.dbjournal.ro/archive/34/34_1.pdf |
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| _version_ | 1850199374366244864 |
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| author | Ion GANEA |
| author_facet | Ion GANEA |
| author_sort | Ion GANEA |
| collection | DOAJ |
| description | This paper presents a holistic approach to biological and agricultural research focused on the use of interconnected technologies in the context of climate change. Researchers from different countries have analyzed how smart technologies can help agriculture adapt to these changes. The most representative works in the field are analyzed. Among these tech-nologies are graph database systems such as Neo4j, which have demonstrated success in predicting the studied phenomena. The paper describes the development of a soybean crop productivity prediction model using monthly and annual data of meteorological phenomena such as precipitation, air temperature, hydrothermal coefficient, soil moisture and others. Some of the results of this promising research are also presented. |
| format | Article |
| id | doaj-art-e592815dc8a048a5b38f29c4e1928df6 |
| institution | OA Journals |
| issn | 2069-3230 |
| language | English |
| publishDate | 2024-05-01 |
| publisher | Bucharest University of Economic Studies |
| record_format | Article |
| series | Database Systems Journal |
| spelling | doaj-art-e592815dc8a048a5b38f29c4e1928df62025-08-20T02:12:38ZengBucharest University of Economic StudiesDatabase Systems Journal2069-32302024-05-01XIV115Prediction Model for Soybean ProductivityIon GANEA0Moldova State University, Chisinau, Republic of MoldovaThis paper presents a holistic approach to biological and agricultural research focused on the use of interconnected technologies in the context of climate change. Researchers from different countries have analyzed how smart technologies can help agriculture adapt to these changes. The most representative works in the field are analyzed. Among these tech-nologies are graph database systems such as Neo4j, which have demonstrated success in predicting the studied phenomena. The paper describes the development of a soybean crop productivity prediction model using monthly and annual data of meteorological phenomena such as precipitation, air temperature, hydrothermal coefficient, soil moisture and others. Some of the results of this promising research are also presented.https://www.dbjournal.ro/archive/34/34_1.pdfholisticknowledgemodelspredictiongraphneo4jgraph data science |
| spellingShingle | Ion GANEA Prediction Model for Soybean Productivity Database Systems Journal holistic knowledge models prediction graph neo4j graph data science |
| title | Prediction Model for Soybean Productivity |
| title_full | Prediction Model for Soybean Productivity |
| title_fullStr | Prediction Model for Soybean Productivity |
| title_full_unstemmed | Prediction Model for Soybean Productivity |
| title_short | Prediction Model for Soybean Productivity |
| title_sort | prediction model for soybean productivity |
| topic | holistic knowledge models prediction graph neo4j graph data science |
| url | https://www.dbjournal.ro/archive/34/34_1.pdf |
| work_keys_str_mv | AT ionganea predictionmodelforsoybeanproductivity |