Just Use a Perceptron to Anticipate Dry

D. K. Sinha, S. Reddy
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Abstract

Drought is considered one of the most terrifying disasters that humanity have ever experienced, and farmers all over the globe often deal with it. It may happen anywhere outside of the globe and is referred to as a “slow catastrophe” since it lasts for a long time, and perhaps even further if it chooses to be more severe. Drought affects also human lives but also crops, global economy, and power that farmers have ingested. During a disaster, seems to be at risk. Basic necessities like food are difficult to get, and market forces imbalance causes irritation to reach its height. There are a variety of things that may be done to prevent the dry, such as desalinating water, crop planning, rainfall gathering, and sprinkler, which can all help preserve water during dry spells. The primary answer to this problem would have been to analyse the environment and the potential results of it, that could aid in planning for the worst-case scenario. Soil predictions may also be very helpful in forecasting this scenario. In order to forecast how floods might be averted, the article combines meteorological and soil data. Deep learning methods will make it possible to determine with remarkable accuracy if the droughts will occur or not.
只需使用感知器来预测干燥
干旱被认为是人类经历过的最可怕的灾难之一,全球各地的农民都经常应对干旱。它可能发生在地球以外的任何地方,被称为“缓慢的灾难”,因为它持续了很长时间,如果它选择更严重的话,可能会持续更长时间。干旱不仅影响人类生活,还影响农作物、全球经济和农民消耗的电力。在一场灾难中,似乎处于危险之中。食品等基本必需品难以获得,市场力量的不平衡导致愤怒达到顶峰。预防干旱的方法有很多,比如海水淡化、作物种植计划、收集雨水和洒水,这些都有助于在干旱时期保持水分。这个问题的主要答案是分析环境及其潜在后果,这有助于为最坏的情况做准备。土壤预测对预测这种情况也很有帮助。为了预测如何避免洪水,文章结合了气象和土壤数据。深度学习方法可以非常准确地确定干旱是否会发生。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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