确定最具生产力的作物,以鼓励使用中性环境的智能农业的可持续耕作方法

A. Abdelhafeez, Hadeer Mahmoud, Alber Aziz
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引用次数: 1

摘要

只有通过精心的管理,农作物提供的数据才能被用来做出明智的、有利可图的选择。数据已经成为当代农业的核心成分,而最近在处理数据方面的进步极大地促进了智能农业的迅速崛起。通过使用传感器收集的客观数据,可以在很大程度上实现效率和寿命的提高。这些数据驱动的农场可以最大限度地提高产量,同时最大限度地减少浪费和环境影响,这要归功于他们收集和分析的信息。智能农业中的各种标准和因素有助于提高生产力。传感器、无人机、全球定位系统(GPS)测绘和其他技术被用于“智能农业”,以跟踪作物生长、土壤质量和天气等变量,以优化产量。这些技术被用于智能农业,以提高可持续性,减少食物浪费,并最大限度地提高农业产量。本文提出了一种平均加权方法来分析和选择智能农业的最佳标准。该方法结合嗜中性集处理不确定数据。本文将可持续性标准作为最佳标准。
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Identify the most Productive Crop to Encourage Sustainable Farming Methods in Smart Farming using Neutrosophic Environment
Only with careful management can the data provided by crops be used to make smart, profitable choices. Data has become the central ingredient in contemporary agriculture, and the recent advancements in handling it are contributing greatly to the meteoric rise of smart farming. Gains in efficiency and longevity may be realized to a significant degree by using the objective data collected by sensors. These data-driven farms can maximize output while minimizing waste and environmental impact thanks to the information they collect and analyze. Various criteria and factors in smart farming can aid in productivity. Sensors, drones, Global Positioning System (GPS) mapping, and other technologies are used in "smart farming" to track variables such as crop development, soil quality, and weather to optimize yields. These technologies are used in smart farming to increase sustainability, decrease food waste, and maximize agricultural yields. This paper suggested a mean weighting methodology to analyze and select the best criteria in smart farming. This method is integrated with the neutrosophic set to deal with uncertain data. This paper achieved the sustainability criteria as the best criteria.
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