Ertragsvorhersage für Weizen durch Clustering und neuronale Netze

The prediction of agricultural yields using data mining tools and techniques is one of the new research areas of recent years. Data mining is an emerging field in the analysis of crop yields. Yield prediction is a very important topic in agriculture. Various seasonal, economic, and biological factors influence plant production, but unpredictable changes in these factors lead to significant losses for farmers. The development of better systems to predict altered effectiveness under different climatic conditions can assist farmers and their staff in the essential initiative of agronomy and crop selection. In agriculture, an efficient framework is required to predict and improve the product worldwide. Due to the inaccessibility of suitable information, the versatile quality of product expectations is high, which affects the nature of the forecasts. In information mining, the grouping of information is the most significant advancement in obtaining profitable insights. This book describes a framework for trim predictions using fuzzy-bunching strategies and neural systems.