Article · Journal of Advanced Computational Intelligence and Intelligent Informatics · May 20, 2014
Integration of Results from Recognition Algorithms Applied to the Uranium Deposits
R. Muhamediyev, Yedilkhan N. Amirgaliyev, S. Iskakov, Yan I. Kuchin, Elena Muhamedijeva
Abstract
Data interpretation of electric logging can be performed using self-learning systems such as artificial neural networks (ANNs). Preliminary research shows that by using ANN we can achieve 52-73% of coincidence of interpretable data and experimental results. Therefore, it is necessary to analyze the possibility of using other classification algorithms, and that of using several classification algorithms simultaneously through a unified system (referred to as anintegrator. These algorithms may improve the quality of recognition of individual species. The problem of developing a recognition system that combines several classification algorithms, also known as theintegrator, is formulated here. A simple algorithm is developed for the learning and recognition of an integrator for the post processing stage; this enhances the recognition accuracy by 1-3%.
More by Yan Kuchin
- MAJOR SOURCES OF FINE PARTICULATE AIR POLLUTION IN FOOTHILL MEGACITY: THE CASE OF ALMATYHydrometeorology and ecology · 2026
- EXPLAINABLE MULTISPECTRAL ATTENTION NETWORK FOR SENTINEL-2 AGRICULTURAL LAND CLASSIFICATIONScientific Journal of Astana IT University · 2026
- SEMANTIC SEGMENTATION OF AGRICULTURAL FIELD ANOMALY PATTERNS IN AERIAL IMAGES USING U-NETHerald of Kazakh-British technical university · 2026
- UAV-Based Classification of Crop Phenological Stages Using Deep LearningDrones · 2026