Scylla属泥蟹形态测定生长及生产条件的K-Means分析平台

Rossian V. Perea, E. Festijo
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引用次数: 0

摘要

传统的电子表格不适合操作和管理与菲律宾泥蟹生产相关的数据集的可视化和分析,因为构建方程以生成所需图表的过程很长。需要一个特定于泥蟹的分析平台来准确地可视化和分析数据集,最终为农民和利益相关者提供更好的数据驱动决策。本文介绍了利用K-means算法的最先进的泥蟹分析平台(MAP)的设计和开发。采用整体系统开发方法,分为三个阶段:1)获取,2)消耗,以及3)集成和转换。因此,MAP能够在描述性、预测性和规范性分析方面提供重要的见解。这个实时动态的分析平台可以为农民和利益相关者提供一个强大的手段,在社区层面上进行数据分析,以获得可操作的见解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Analytics Platform for Morphometric Grow out and Production Condition of Mud Crabs of the Genus Scylla with K-Means
The traditional use of an electronic spreadsheet is poorly suited to operationalize and manage the visualization and analysis of datasets related to mud crab production in the Philippines because of the long process of constructing equations to produce the desired diagram. A mud crab-specific analytic platform is needed to accurately visualize and analyze the datasets that will eventually result in better and data-driven decision-making on the part of farmers and stakeholders. This paper introduces the design and development of a state-of-the-art Mud crab Analytics Platform (MAP) utilizing the K-means algorithm. A holistic system development approach was applied which consists of three phases namely; 1) capture, 2) consumption, and 3) integration and transformation. As a result, MAP was able to provide significant insights in terms of descriptive, predictive, and prescriptive analytics. This real-time and dynamic analytic platform may provide farmers and stakeholders a powerful means to conduct data analysis on a community level to obtain actionable insights.
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