USE OF OLAP AND DATA MINING TECHNOLOGIES IN DECISION SUPPORT SYSTEMS IN GREENHOUSE FARMING
DOI:
https://doi.org/10.31548/itees.2024.01.008Keywords:
decision support system, OLAP, Data Mining, data warehouse, multidimensional cubeAbstract
In the modern world, technologies play a key role in many areas of life, including agriculture. Growing vegetables and fruits in closed ground structures is becoming increasingly popular and requires control over conditions and resources to increase yields, however, with the increase in the amount of data collected in monitoring systems, it becomes more difficult to effectively analyze the collected information.
This article considers the use of OLAP and Data Mining technologies to increase the efficiency of growing vegetables and fruits in closed ground structures. The purpose of the study is to determine the feasibility and effectiveness of using these technologies to analyze large amounts of data collected during the cultivation of vegetables and fruits. The authors of the study analyze how OLAP and Data Mining can provide useful information for making decisions on optimizing growing processes to increase yields.
References
1. Wang, C., Wang, L., Dong, P., Qiao, X. (2008). Research of Decision Support System (DSS) for Greenhouse Based on Data Mining. In: Li, D. (eds) Computer And Computing Technologies In Agriculture, Volume II. CCTA 2007. The International Federation for Information Processing, vol 259. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-77253-0_40.
2. Hu, Y., Wang, J., & Li, P. (2010). Expert System for Greenhouse Production Management. In Expert Systems. InTech. https://doi.org/10.5772/7080.
3. Microsoft. (2023). Data mining concepts. Analysis Services. https://docs.microsoft.com/en-us/analysis-services/data-mining/data-mining-concepts?view=asallproducts-allversions
4. TutorialsPoint. (2022). What are the basic concepts of data mining. https://www.tutorialspoint.com/what-are-the-basic-concepts-of-data-mining
5. Microsoft. (2024). Overview of online analytical processing (OLAP). Microsoft Support. https://support.microsoft.com/en-us/office/overview-of-online-analytical-processing-olap-15d2cdde-f70b-4277-b009-ed732b75fdd6
6. Microsoft. (2024). Data source views in multidimensional models. Analysis Services. https://docs.microsoft.com/en-us/analysis-services/multidimensional-models/data-source-views-in-multidimensional-models?view=asallproducts-allversions
7. Microsoft. (2024). Key performance indicators (KPIs) in multidimensional models. Analysis Services. https://docs.microsoft.com/en-us/analysis-services/multidimensional-models/key-performance-indicators-kpis-in-multidimensional-models?view=asallproducts-allversions
8. Greenhouse Grower. (2011). Monitoring the greenhouse environment. https://www.greenhousegrower.com/production/plant-culture/special-series/monitoring-the-greenhouse-environment/
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