Towards Single Value Coordinate System (SVCS) for Earthquake Forecasting Using Single Layer Hierarchical Graph Neuron (SLHGN)
International audience 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...
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ftunivnantes:oai:HAL:hal-03761630v1 2023-05-15T17:39:57+02:00 Towards Single Value Coordinate System (SVCS) for Earthquake Forecasting Using Single Layer Hierarchical Graph Neuron (SLHGN) Nasution, Benny, Sembiring, Rahmat, Siregar, Indra Seri, Ermyna Mardi, Rina Politeknik Negeri Medan Yuko Murayama Dimiter Velev Plamena Zlateva TC 5 WG 5.15 Sofia, Bulgaria 2020-12-03 https://hal.inria.fr/hal-03761630 https://hal.inria.fr/hal-03761630/document https://hal.inria.fr/hal-03761630/file/498235_1_En_7_Chapter.pdf https://doi.org/10.1007/978-3-030-81469-4_7 en eng HAL CCSD Springer International Publishing info:eu-repo/semantics/altIdentifier/doi/10.1007/978-3-030-81469-4_7 hal-03761630 https://hal.inria.fr/hal-03761630 https://hal.inria.fr/hal-03761630/document https://hal.inria.fr/hal-03761630/file/498235_1_En_7_Chapter.pdf doi:10.1007/978-3-030-81469-4_7 http://creativecommons.org/licenses/by/ IFIP Advances in Information and Communication Technology 5th International Conference on Information Technology in Disaster Risk Reduction (ITDRR) https://hal.inria.fr/hal-03761630 5th International Conference on Information Technology in Disaster Risk Reduction (ITDRR), Dec 2020, Sofia, Bulgaria. pp.73-89, ⟨10.1007/978-3-030-81469-4_7⟩ Earthquake forecasting Single Layer Hierarchical Graph Neuron (SLHGN) Single Value Coordinate System (SVCS) Hierarchical Graph Neuron (HGN) [INFO]Computer Science [cs] info:eu-repo/semantics/conferenceObject Conference papers 2020 ftunivnantes https://doi.org/10.1007/978-3-030-81469-4_7 2022-08-30T22:45:33Z International audience 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. Conference Object North Pole Université de Nantes: HAL-UNIV-NANTES North Pole 73 89 |
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Open Polar |
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Université de Nantes: HAL-UNIV-NANTES |
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ftunivnantes |
language |
English |
topic |
Earthquake forecasting Single Layer Hierarchical Graph Neuron (SLHGN) Single Value Coordinate System (SVCS) Hierarchical Graph Neuron (HGN) [INFO]Computer Science [cs] |
spellingShingle |
Earthquake forecasting Single Layer Hierarchical Graph Neuron (SLHGN) Single Value Coordinate System (SVCS) Hierarchical Graph Neuron (HGN) [INFO]Computer Science [cs] Nasution, Benny, Sembiring, Rahmat, Siregar, Indra Seri, Ermyna Mardi, Rina Towards Single Value Coordinate System (SVCS) for Earthquake Forecasting Using Single Layer Hierarchical Graph Neuron (SLHGN) |
topic_facet |
Earthquake forecasting Single Layer Hierarchical Graph Neuron (SLHGN) Single Value Coordinate System (SVCS) Hierarchical Graph Neuron (HGN) [INFO]Computer Science [cs] |
description |
International audience 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. |
author2 |
Politeknik Negeri Medan Yuko Murayama Dimiter Velev Plamena Zlateva TC 5 WG 5.15 |
format |
Conference Object |
author |
Nasution, Benny, Sembiring, Rahmat, Siregar, Indra Seri, Ermyna Mardi, Rina |
author_facet |
Nasution, Benny, Sembiring, Rahmat, Siregar, Indra Seri, Ermyna Mardi, Rina |
author_sort |
Nasution, Benny, |
title |
Towards Single Value Coordinate System (SVCS) for Earthquake Forecasting Using Single Layer Hierarchical Graph Neuron (SLHGN) |
title_short |
Towards Single Value Coordinate System (SVCS) for Earthquake Forecasting Using Single Layer Hierarchical Graph Neuron (SLHGN) |
title_full |
Towards Single Value Coordinate System (SVCS) for Earthquake Forecasting Using Single Layer Hierarchical Graph Neuron (SLHGN) |
title_fullStr |
Towards Single Value Coordinate System (SVCS) for Earthquake Forecasting Using Single Layer Hierarchical Graph Neuron (SLHGN) |
title_full_unstemmed |
Towards Single Value Coordinate System (SVCS) for Earthquake Forecasting Using Single Layer Hierarchical Graph Neuron (SLHGN) |
title_sort |
towards single value coordinate system (svcs) for earthquake forecasting using single layer hierarchical graph neuron (slhgn) |
publisher |
HAL CCSD |
publishDate |
2020 |
url |
https://hal.inria.fr/hal-03761630 https://hal.inria.fr/hal-03761630/document https://hal.inria.fr/hal-03761630/file/498235_1_En_7_Chapter.pdf https://doi.org/10.1007/978-3-030-81469-4_7 |
op_coverage |
Sofia, Bulgaria |
geographic |
North Pole |
geographic_facet |
North Pole |
genre |
North Pole |
genre_facet |
North Pole |
op_source |
IFIP Advances in Information and Communication Technology 5th International Conference on Information Technology in Disaster Risk Reduction (ITDRR) https://hal.inria.fr/hal-03761630 5th International Conference on Information Technology in Disaster Risk Reduction (ITDRR), Dec 2020, Sofia, Bulgaria. pp.73-89, ⟨10.1007/978-3-030-81469-4_7⟩ |
op_relation |
info:eu-repo/semantics/altIdentifier/doi/10.1007/978-3-030-81469-4_7 hal-03761630 https://hal.inria.fr/hal-03761630 https://hal.inria.fr/hal-03761630/document https://hal.inria.fr/hal-03761630/file/498235_1_En_7_Chapter.pdf doi:10.1007/978-3-030-81469-4_7 |
op_rights |
http://creativecommons.org/licenses/by/ |
op_doi |
https://doi.org/10.1007/978-3-030-81469-4_7 |
container_start_page |
73 |
op_container_end_page |
89 |
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1766140719552004096 |