Archive | 2019

Crop Yield Prediction Using Deep Learning in Mediterranean Region

 
 
 
 

Abstract


Knowledge of meteorological or climatic data in a region is essential for the successful development of agriculture, energy and sustainable development in this region. The main goal of this article is the proper use of the data mining technique for meteorological and agricultural data to help in the development of agriculture in Mediterranean region. study of meteorological data affected by climate change using a data mining technique such as clustering technique by combining with knowledge base constructed from climate rules adapted to a specific agricultural crop. Using this technique, we can acquire new information that can help predict the future quality of the yield of this crop and sought to improve its production, the model built from the large dataset transfers the information retrieved in usable knowledge for classification and forecasting of climatic conditions. We discussed the use of a data mining technique to analyze meteorological and agricultural data. Various data extraction tools and techniques are already available, but they have been used in a very limited way for meteorological data and are never combined with a knowledge dataset adapted to a specific agriculture culture. In this paper, an algorithm based on a network of neurons to predict the impact of climate change on the production and yields of some agricultural crops for a future time and a given site.

Volume None
Pages None
DOI 10.1007/978-3-030-36664-3_12
Language English
Journal None

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