Towards Single Value Coordinate System (SVCS) for Earthquake Forecasting Using Single Layer Hierarchical Graph Neuron (SLHGN)
Abstract
The current coordinate system has been the major challenge for the development of earthquake forecasting technology using Single Layer Hierarchical Graph Neuron (SLHGN). First, the accuracy of the longitude value is not distributed equally, and the accuracy gets worse towards the poles. Second, the distance of the same longitude difference varies following the difference of the latitude values. The extreme one is again on the poles, where the longitude value becomes unity. Third, there is no way to have a coordinate of an area. As an alternative the Single Value Coordinate System (SVCS) has been scrutinized and elaborated. The coordinate system treats every area on the earth equally on the equator until the poles. It means that the accuracy is everywhere the same and the calculation of a distance and an area is not dependent on the location (e.g. near the equator, near the North Pole, etc.). At this stage the algorithm for measuring a distance and the conversion from and to the current coordinate system are available. The distance between two locations is directly discovered from the value of the coordinate itself. The coordinate system is fundamentally dedicated to pinpoint an area, not a point. The smaller an area is the more precise the location will be. Using the SVCS, the characteristic of the earth as a spherical shape suits the SLHGN architecture.
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