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2020 | OriginalPaper | Chapter

Historical Weather Data Recovery and Estimation

Authors : Fadoua Rafii, Tahar Kechadi

Published in: Innovations in Smart Cities Applications Edition 3

Publisher: Springer International Publishing

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Abstract

In order to make efficient decisions in agriculture, it is imperative to analyse the weather data collected from various sources. These data are generated by automated weather stations. Unfortunately, weather observations may be missing or altered since weather stations may be stopped for maintenance or became out of order. Thus, it would affect significantly the process of data analysis. The purpose of this study is to estimate those missing values by using interpolation methods and others. We study the effectiveness of each method and compare them on different weather attributes. The methods were applied on different patterns of missing values and outliers. The experimental results prove that the two methods based on geographical proximity are performing better.

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Metadata
Title
Historical Weather Data Recovery and Estimation
Authors
Fadoua Rafii
Tahar Kechadi
Copyright Year
2020
Book
Innovations in Smart Cities Applications Edition 3

Print ISBN: 978-3-030-37628-4

Electronic ISBN: 978-3-030-37629-1

Copyright Year: 2020

DOI
https://doi.org/10.1007/978-3-030-37629-1_85

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