Reasoning of Spatial Relation Between Curves by Neural Network
利用人工神经网络推断曲线间的空间关系

In the field of synthetic information forecast for mineral product, extremum lines (curves) of the first order differential coefficient of aeromagnetic and gravitational maps reflect the ruptures of magnetism and the densities of geologic bodies respectively. In order to deduce the rupture conformation, the similarities of attitude and size of geologic bodies in different deepness, curves of aeromagnetic and gravitational maps in different deepness and directions must be compared; only those ruptures of reflection with similar curves are reliable. In order to deduce and analyze the situation automatically, in this paper, we first introduced the conventional estimation approach of spatial relation between curves. Later on, we also described the Neural Networks approach of reasoning of spatial relation between curves. The result indicate that these estimations of spatial relations between curves obtained by the Neural Networks approaches matched perfectly with the estimations of authoritative geological experts, and achieved triumphs in practical applications.