SMART AND INTELLIGENT PRODUCTION STRATEGY FOR THE FLOWER MARKET USING DATA MINING KNOWLEDGE-BASED DECISION

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Abstract

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.
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基于数据挖掘知识的花卉市场智能生产策略决策
农业产业已成为生产和消费市场价值链中的巨大经济支柱。随着农业技术革命,农业产业对花卉生产要素进行了重置。最快的技术为季节性切花提供创新和智能的决策策略,以提高产量。本研究概述了现有的耕作方式、连锁活动和耕作技术对农田和园林产业的重大影响。作者试图调查切花生产现状,分析生产价值,设计创新和智能的策略,特别是季节性花卉生产。该研究采用了花卉数据集;因此,它应用花卉参数输入和数据挖掘关联规则来创建一个适合于评估特定季节花卉市场产值的花卉生产类别的输出。研究结果表明,本文提出的花卉生产策略为根据市场需求增加花卉生产提供了高效、智能的指导。本研究为花农提出智慧友善的生产策略,让花市能持续且有品质的生产,以满足消费者即时的市场需求。
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