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SPAS-Dataset-BD:孟加拉国智能精密农业系统的数据集

Rup Chowdhury¹, Fernaz Narin Nur¹, Muhammad Nazrul Islam¹

¹Department of Computer Science and Engineering, Military Institute of Science and Technology, Mirpur Cantonment, Dhaka, 1216, Bangladesh.

|June 27, 2025

概括

一个新的数据集,SPAS-Dataset-BD,解决了孟加拉国精密农业局部数据的缺乏. 它支持机器学习用于作物分类和产量预测,增强农业的可持续性.

科学领域:

农业科学农业科学
数据科学数据科学数据科学
环境科学环境科学

背景情况:

精准农业依赖于数据,但像孟加拉国这样的低收入国家缺乏特定区域的数据集.
现有的数据往往无法捕捉到当地农业气候条件和农业做法.

研究的目的:

推出SPAS-Dataset-BD,这是孟加拉国精密农业的综合数据集.
为南亚农业的研究和政策制定提供一个强大的,本地化的数据资源.

主要方法:

这是一种混合方法,它结合了孟加拉国统计局 (BBS) 2022 年度年鉴和初级现场调查的二次数据.
数据收集涉及10个地区的223名农民,涵盖了73种作物类型和12种特征.
通过处理缺失值,删复和与官方统计数据进行交叉验证来确保数据的稳定性.

主要成果:

SPAS-Dataset-BD包含4191个记录,详细的农业和环境特征.
证明了数据集的稳定性和适用于机器学习应用的适用性.
突出了在73类作物分类,产量预测和基于物联网的灌计划中的潜在用途.

结论:

SPAS-Dataset-BD是南亚精准农业的一个有价值,大规模和方法上透明的资源.
数据集的背景丰富性支持本地化农业研究和明智的政策决策.
促进了数据驱动农业实践和资源优化方面的进步.

关键词:

农业数据集农业数据集孟加拉国孟加拉国孟加拉国预测作物的预测.这就是为什么物联网是物联网物联网.机器学习是机器学习.精准农业精准农业精准农业

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