Akademik Veri Yönetim Sistemi
Journal of Scientific and Engineering Research, cilt.9, sa.7, ss.105-115, 2022 (Hakemli Dergi)
Abstract In this paper, Random Neural Network (RNN) has been applied to magnetic map for separation of
residual and regional anomalies. It is shown that RNN is the appropriate approach for the prior real-time model
since it can perfectly specify the local properties of regions. Additional domain-dependent prior knowledge,
such as the sizes, the shapes, the depth and the orientations of regions can be reflected in the parameters of a
RNN model. RNN approach has been applied to various synthetic examples. The RNN method was applied to
the bouguer anomaly map obtained in the Dumluca iron mine area of Sivas region in Turkey. The resulting
anomalies were then compared with the drilling data and successful results were obtained.
Keywords Random Neural Network (RNN), Iron Ore, Bouguer anomaly map, Sivas-Turkey