Machine Learning in Python for Weather Forecast based on Freely Available Weather Data

E. B. Abrahamsen, O. M. Brastein, B. Lie
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引用次数: 28

Abstract

Forecasting weather conditions is important for, e.g., operation of hydro power plants and for flood management. Mechanistic models are known to be computationally demanding. Hence, it is of interest to develop models that can predict weather conditions faster than traditional meteorological models. The field of machine learning has received much interest from the scientific community. Due to its applicability in a variety of fields, it is of interest to study whether an artificial neural network can be a good candidate for prediction of weather conditions in combination with large data sets. The availability of meteorological data from multiple online sources is an advantage. In order to simplify the retrieval of data, a Python API to read meteorological data has been developed, and ANN models have been developed using TensorFlow.
基于免费天气数据的Python天气预报机器学习
预报天气状况对水力发电厂的运作和洪水管理等方面都很重要。众所周知,机械模型的计算要求很高。因此,开发能够比传统气象模型更快地预测天气状况的模型是人们感兴趣的。机器学习领域已经引起了科学界的极大兴趣。由于其在各个领域的适用性,研究人工神经网络是否可以很好地结合大数据集预测天气状况是一个有趣的选择。从多个在线来源获得气象数据是一个优势。为了简化数据检索,开发了一个Python API来读取气象数据,并使用TensorFlow开发了人工神经网络模型。
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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