Enhancing Temperature Data Quality for Agricultural Decision-Making with Emphasis to Evapotranspiration Calculation: A Robust Framework Integrating Dynamic Time Warping, Fuzzy Logic, and Machine Learning

Enhancing Temperature Data Quality for Agricultural Decision-Making with Emphasis to Evapotranspiration Calculation: A Robust Framework Integrating Dynamic Time Warping, Fuzzy Logic, and Machine Learning

This study introduces a comprehensive framework for assessing and enhancing the quality of hourly temperature data collected from a six-station agrometeorological network in the Arta plain, Epirus, Greece, spanning the period 2015–2023. By combining traditional quality control (QC) techniques with a...

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Bibliographic Details
Main Authors: Christos Koliopanos, Alexandra Gemitzi, Petros Kofakis, Nikolaos Malamos, Ioannis Tsirogiannis
Format: Article
Language:English
Published: MDPI AG 2025-06-01
Series:AgriEngineering
Subjects:
anomaly detection
Dynamic Time Warping (DTW)
Fuzzy Logic
XGBoost
spatiotemporal analysis
irrigation scheduling
Online Access:https://www.mdpi.com/2624-7402/7/6/174
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