Rainfall Prediction Using Machine Learning

Akash Gupta, Hitesh Kumar Mall, S. Janarthanan
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引用次数: 15

Abstract

Rainfall forecasting is a single of difficult and unpredictable undertakings that has a major influence on human society. Predictions that are accurate and timely can help to avert human and financial loss. This study contains a series of experiments that include the utilisation of basic machine learning techniques to build Weather forecasting models that estimate whether it will rain in major cities tomorrow based on the day’s meteorological data. This comparative research looks at three aspects of modelling inputs, modelling methodologies, and preprocessing procedures. The findings demonstrate how different machine learning systems perform on a range of assessment parameters, as well as their capacity to forecast rainfall using weather data analysis. Agriculture is crucial to India’s survival. The importance of rainfall in agriculture cannot be overstated. Rainfall forecasting has been a key problem in recent years. Individuals can be more aware of the weather and make more educated judgments by predicting rainfall.
使用机器学习进行降雨预测
降雨预报是一项对人类社会有重大影响的困难和不可预测的工作。准确和及时的预测有助于避免人员和经济损失。这项研究包含了一系列的实验,包括利用基本的机器学习技术来建立天气预报模型,根据当天的气象数据估计明天主要城市是否会下雨。这项比较研究着眼于建模输入、建模方法和预处理程序的三个方面。研究结果展示了不同的机器学习系统在一系列评估参数上的表现,以及它们利用天气数据分析预测降雨的能力。农业对印度的生存至关重要。降雨对农业的重要性怎么强调也不为过。近年来,降雨预报一直是一个关键问题。个人可以更了解天气,并通过预测降雨做出更有根据的判断。
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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