印度各邦降雨的新研究和使用机器学习算法的预测分析

Nikhil Tiwari, A. Singh
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引用次数: 3

摘要

在像印度这样的农业国家,收成的成败在很大程度上取决于该国的降雨模式。印度的农业生产高度依赖于季风降雨的降水行为。季风是印度的主要水源。平均降雨量预测是作物规划的一个重要因素。许多研究显示了雨水对农作物的直接影响。本研究利用机器学习技术和算法对印度各邦的降雨模式进行了研究,该研究利用了1901年至2017年政府提供的降雨数据。本研究提出使用机器学习算法对印度各邦的降雨进行研究和分析,并将其性能与标准结果进行比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Novel Study of Rainfall in the Indian States and Predictive Analysis using Machine Learning Algorithms
In an agricultural country like India, the success or failure of the harvest is highly dependent on the rainfall pattern of the country. India’s agriculture production is highly dependent on its precipitation behavior of the monsoon rainfall. Monsoon is the main source of water in India. Average rainfall prediction is a prime important factor for crop planning. Many of the studies have shown the direct influence of rainwater on the crops. This research has conducted a study on rainfall pattern in Indian states using machine learning techniques and algorithms, which utilizes government provided rainfall data from 1901-2017. This research proposes a study and analysis of rainfall in the Indian states using machine learning algorithms and compared their performances to the standard results.
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