Improved resolution of the multiple inverse method by eliminating erroneous solutions |
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| Affiliation: | 1. Department of Chemistry, Christopher Ingold Laboratories, University College London, 20 Gordon Street, London WC1H 0AJ, United Kingdom;2. School of Engineering and Materials Science, Queen Mary University of London, Mile End Road, London E1 4NS, United Kingdom;1. Consiglio Nazionale delle Ricerche – Istituto per la Microelettronica e Microsistemi (CNR-IMM), via Monteroni c/o Campus Universitario, I-73100 Lecce, Italy;2. SENSOR Lab, Department of Information Engineering, Brescia University and CNR-INO, via Valotti, 9, 25133 Brescia, Italy;3. Institute for Energy Research (IREC), Jardí de les Dones de Negre, 1, E-08930 Sant Adrià del Besos, Barcelona, Spain;4. Departament d’Electrònica, Universitat de Barcelona, C.\\ Martí i Franquès 1, E-08028 Barcelona, Spain;1. CINSO (Solid State Research Dept.) CITEDEF, UNIDEF (MINDEF-CONICET), Juan B. de La Salle 4397, Villa Martelli, B1603 ALO Buenos Aires, Argentina;2. Microelectronics, Thin Films Laboratory – CITEDEF, Juan B. de La Salle 4397, Villa Martelli, B1603 ALO Buenos Aires, Argentina;1. King Saud University, Faculty of Science, Geology and Geophysics Department, Riyadh, Saudi Arabia;2. Department of Geophysics, Kangwon National University, Chunchon, Republic of Korea;3. Department of Seismology, National Research Institute of Astronomy and Geophysics, 11421 Helwan, Cairo, Egypt;1. Department of Applied Geophysics, Indian School of Mines, Dhanbad 826004, Jharkhand, India;2. Institute of Seismological Research, Gandhinagar 382009, Gujarat, India;3. Department of Applied Geology, Indian School of Mines, Dhanbad, Jharkhand 826004, India;4. Department of Civil Engineering, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece |
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| Abstract: | The multiple inverse method is a numerical technique designed to separate stresses from heterogeneous fault–slip data. The method is one of the resampling methods based on the pattern recognition. Plotting solutions determined from k-fault subset into the parameter space, we have clusters representing significant stresses for the dataset. This paper presents a technique to improve the resolution of stress for the method. The regularity/singularity test of the subsets taken from the fault–slip data is the key for this purpose. The resolution and accuracy of the method are improved by eliminating erroneous stresses or artifacts that were yielded by the method. The performances of the method are demonstrated with a variety of artificial datasets. |
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