随机森林与决策树预测发电系统太阳辐射的比较分析

Sasirekha P, Navinkumar T M, Anton Amala Praveen A, Bharani Prakash T, Swapna P, M. Vinothkumar
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引用次数: 0

摘要

在不可再生能源发电中,太阳辐射估算对太阳能发电系统的开发和设计具有重要意义。但是由于一些技术问题和测量技术的成本,全球太阳辐射的数据集并不容易在印度所有地方获得。因此,通过输入时间、辐射、温度、压力、湿度、风向、速度、日出时间和日落时间等参数来预测太阳辐射是很重要的。本文着重分析了随机森林技术在太阳辐射预报中的应用。这一分析为使用机器学习算法预测性能提供了更清晰的知识。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Comparative Analysis of Prediction on Solar Radiation in Energy Generation System using Random Forest and Decision Tree
The solar radiation estimation is very important for developing and design of solar energy production system in generation of non-renewable energy. But the data set of Global solar radiation is not easily obtainable in all places of India due to some technical issues and cost in measurement technologies. Consequently it is important to forecasting the solar radiation prediction using some techniques by input parameters namely Time, Radiation, Temperature, Pressure, Humidity, Wind Direction, Speed, Time Sun rise and Time sun set. In this paper the author focused on analyzing the solar radiation prediction using Random Forest technique. This analysis gives more clear knowledge in prediction performance using machine learning algorithms.
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