• Tanjea Ane Assistant Professor, Department of Computer Science and Information Technology, Faculty of Agriculture, Bangabandhu Sheikh Mujibur Rahman Agricultural University, Salna, Gazipur-1706, Bangladesh
  • Tabatshum Nepa Department of Social Policy, School of History and Social Sciences, Bangor University, Bangor, Gwynedd, North Wales, LL57 2DG, United Kingdom
  • Mahfuzur Rahman Khan Department of Business Administration, Faculty of Bachelor of Business Administration, University of Asia Pacific, Bangladesh
Keywords: Production Strategy, Computer Application, Data Mining, Knowledge Based Decision, Association Rule.


The agriculture industry has been an enormous economic pillar in the production and consumption market value chain. The agriculture industry resets flower production factors with the agricultural technology revolution. The fastest technology provides innovative and intelligent decision-making strategies in seasonal cut flowers to increase production. This study briefs out existing farming practices, chain activity and farming technology’s significant impacts on the agriculture field and garden industry. Authors try to investigate cut flower production status and analyze production values to design innovative and intelligent strategies, especially for seasonal flower production. The study employs a flower dataset; hence, it applies floral parameter inputs and data mining association rules to create an output of the flower production category, which fits appropriately to evaluate flower market production value in a particular season. The article's result reveals that the proposed flower production strategy provides efficient and intelligent guidelines to increase flower production according to market demand. This study suggests an intelligent and friendly production strategy for gardeners that indicates the flower market gets continuous and quality production to meet consumers’ immediate market demand.   

JEL Classification Codes: Q130, Q160, Q180.


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How to Cite
Ane, T., Nepa, T., & Khan, M. R. (2023). SMART AND INTELLIGENT PRODUCTION STRATEGY FOR THE FLOWER MARKET USING DATA MINING KNOWLEDGE-BASED DECISION. Bangladesh Journal of Multidisciplinary Scientific Research, 7(1), 35-43.
Research Paper/Theoretical Paper/Review Paper/Short Communication Paper