A multi-layer quality control tool for weather-driven agricultural decision support models.

摘要

Weather plays an important role in agriculture. This calls for reliable weather data, which in turn runs agricultural decision support systems that help farmers make management decisions about their crops. It is well known that "garbage in means garbage out". The presence of anomalies and errors in a weather dataset can gravely compromise the results given by various applications using them. Moreover, many of these applications cannot handle datasets with missing entries and just simply crash. Thus, to have seamless operation and obtain meaningful, accurate results from agricultural decision support systems, it is essential to have a clean and complete set of data. For my M.Sc. thesis, I propose a multi-layer quality control tool for weather data. This multi-purpose quality control tool enhances agricultural decision support systems and eventually improves the farmer's decision-making capability on the management of his crops. Experimental results on real-life datasets show the positive effects of our tool on the quality control of agro-meteorological data.