利用数据科学分析和预测全球变暖

M. Purushotham Reddy, A. Aneesh, K. Praneetha, S. Vijay
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引用次数: 5

摘要

本文分析了机器学习算法的呈现,线性回归预测全球温度和前几年在印度收集的数据的碳排放。对长期全球变暖和天气状况的预测在气候研究、农业、电力、医药等许多领域都具有重大意义。这些数据是通过线性回归计算和预测的,因为在所有可以使用的技术中,它对全球变暖和温度的精度最高。第一步是在广泛的数据集上设计一个一致、有效、可靠的统计数据模型,最终得出年平均气温与全球变暖因素之间的关系。全球气温下降将使整个地球受益,因为不仅人类而且各种动物都受到全球变暖的影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Global Warming Analysis and Prediction Using Data Science
This paper analyzes the presentation of the machine learning algorithm, linear regression for prediction of global temperature and carbon emissions from previous years collected data over India. The forecast of long-term global warming and weather conditions could be of huge significance in various fields, such as climate research, farming, electricity, medicine, and many more. The data is calculated and predicted by linear regression since, of all the techniques that can be used, it obtains the highest precision for global warming and temperature. First ever step is to design a consistent, effective, reliable statistical data model on a broad data set and ultimately bring the relationship between average annual temperature and contributing factors to global warming. Global temperature reduction will benefit the entire globe because not only Humans but also various animals suffer from global warming.
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