Intelligent Data Mining and Fusion Systems in Agriculture presents methods of computational intelligence and data fusion that have applications in agriculture for the non-destructive testing of agricultural products and crop condition monitoring. Sections cover the combination of sensors with artificial intelligence architectures in precision agriculture, including algorithms, bio-inspired hierarchical neural maps, and novelty detection algorithms capable of detecting sudden changes in different conditions. This book offers advanced students and entry-level professionals in agricultural science and engineering, geography and geoinformation science an in-depth overview of the connection between decision-making in agricultural operations and the decision support features offered by advanced computational intelligence algorithms. – Covers crop protection, automation in agriculture, artificial intelligence in agriculture, sensing and Internet of Things (Io Ts) in agriculture- Addresses AI use in weed management, disease detection, yield prediction and crop production- Utilizes case studies to provide real-world insights and direction
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