Bayesian network methodology for decision support in forensic geotechnical engineering
ilustraciones, diagramas
- Autores:
-
Garcia Feria, William Mauricio
- Tipo de recurso:
- Doctoral thesis
- Fecha de publicación:
- 2023
- Institución:
- Universidad Nacional de Colombia
- Repositorio:
- Universidad Nacional de Colombia
- Idioma:
- eng
- OAI Identifier:
- oai:repositorio.unal.edu.co:unal/84789
- Palabra clave:
- 620 - Ingeniería y operaciones afines::624 - Ingeniería civil
Teoría bayesiana de decisiones estadísticas
Decisiones estadísticas
Bayesian statistical decision theory
Statistical decision
Forensic geotechnical engineering
Bayesian inference
Bayesian Networks
- Rights
- openAccess
- License
- Reconocimiento 4.0 Internacional
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| dc.title.eng.fl_str_mv |
Bayesian network methodology for decision support in forensic geotechnical engineering |
| dc.title.translated.spa.fl_str_mv |
Metodología de redes bayesianas para apoyar la toma de decisiones en ingeniería geotécnica forense |
| title |
Bayesian network methodology for decision support in forensic geotechnical engineering |
| spellingShingle |
Bayesian network methodology for decision support in forensic geotechnical engineering 620 - Ingeniería y operaciones afines::624 - Ingeniería civil Teoría bayesiana de decisiones estadísticas Decisiones estadísticas Bayesian statistical decision theory Statistical decision Forensic geotechnical engineering Bayesian inference Bayesian Networks |
| title_short |
Bayesian network methodology for decision support in forensic geotechnical engineering |
| title_full |
Bayesian network methodology for decision support in forensic geotechnical engineering |
| title_fullStr |
Bayesian network methodology for decision support in forensic geotechnical engineering |
| title_full_unstemmed |
Bayesian network methodology for decision support in forensic geotechnical engineering |
| title_sort |
Bayesian network methodology for decision support in forensic geotechnical engineering |
| dc.creator.fl_str_mv |
Garcia Feria, William Mauricio |
| dc.contributor.advisor.none.fl_str_mv |
Colmenares Montañez, Julio Esteban |
| dc.contributor.author.none.fl_str_mv |
Garcia Feria, William Mauricio |
| dc.contributor.researchgroup.spa.fl_str_mv |
GENKI - Geotechnical Engineering Knowledge and Innovation |
| dc.contributor.orcid.spa.fl_str_mv |
Garcia-Feria, William Mauricio [0000-0002-4407-5579] |
| dc.contributor.cvlac.spa.fl_str_mv |
Garcia, William Mauricio |
| dc.contributor.researchgate.spa.fl_str_mv |
Garcia-Feria, Mauricio |
| dc.contributor.googlescholar.spa.fl_str_mv |
Garcia-Feria, Mauricio |
| dc.subject.ddc.spa.fl_str_mv |
620 - Ingeniería y operaciones afines::624 - Ingeniería civil |
| topic |
620 - Ingeniería y operaciones afines::624 - Ingeniería civil Teoría bayesiana de decisiones estadísticas Decisiones estadísticas Bayesian statistical decision theory Statistical decision Forensic geotechnical engineering Bayesian inference Bayesian Networks |
| dc.subject.lemb.spa.fl_str_mv |
Teoría bayesiana de decisiones estadísticas Decisiones estadísticas |
| dc.subject.lemb.eng.fl_str_mv |
Bayesian statistical decision theory Statistical decision |
| dc.subject.proposal.eng.fl_str_mv |
Forensic geotechnical engineering Bayesian inference Bayesian Networks |
| description |
ilustraciones, diagramas |
| publishDate |
2023 |
| dc.date.accessioned.none.fl_str_mv |
2023-10-09T15:41:28Z |
| dc.date.available.none.fl_str_mv |
2023-10-09T15:41:28Z |
| dc.date.issued.none.fl_str_mv |
2023 |
| dc.type.spa.fl_str_mv |
Trabajo de grado - Doctorado |
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info:eu-repo/semantics/doctoralThesis |
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info:eu-repo/semantics/acceptedVersion |
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http://purl.org/coar/resource_type/c_db06 |
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Text |
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http://purl.org/redcol/resource_type/TD |
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http://purl.org/coar/resource_type/c_db06 |
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acceptedVersion |
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https://repositorio.unal.edu.co/handle/unal/84789 |
| dc.identifier.instname.spa.fl_str_mv |
Universidad Nacional de Colombia |
| dc.identifier.repo.none.fl_str_mv |
Repositorio Institucional Universidad Nacional de Colombia |
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https://repositorio.unal.edu.co/ |
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https://repositorio.unal.edu.co/handle/unal/84789 https://repositorio.unal.edu.co/ |
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Universidad Nacional de Colombia Repositorio Institucional Universidad Nacional de Colombia |
| dc.language.iso.spa.fl_str_mv |
eng |
| language |
eng |
| dc.relation.references.spa.fl_str_mv |
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Verhulst (Eds.), Guidelines for Failure Investigation. https://doi.org/10.1061/9780784415122 Babu, G. L. S. (2016). Briefing: Forensic geotechnical engineering. Proceedings of the Institution of Civil Engineers - Forensic Engineering, 1–4. Babu, G. L., & Singh, V. P. (2016). Back Analyses in Geotechnical Engineering (V. V. S. Rao & G. L. Sivakumar Babu (Eds.); pp. 113–118). Springer India. https://doi.org/10.1007/978- 81-322-2377-1_7 Babu, G., Raja, J., Munwar Basha, B., & Srivastava, A. (2016). Forensic Analysis of Failure of Retaining Wall. In V. V. S. Rao & G. L. Sivakumar Babu (Eds.), Forensic Geotechnical Engineering (pp. 451–465). Springer India. https://doi.org/10.1007/978-81-322-2377-1_30 Baecher, G. B. (2017). Bayesian Thinking in Geotechnics. Geo-Risk 2017, June, 1–18. https://doi.org/10.1061/9780784480694.001 Baecher, G. B., & Christian, J. T. (2003). Reliability and statistics in geotechnical engineering (Issue 1). 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Bulletin of Engineering Geology and the Environment, 57(1), 91–99. https://doi.org/10.1007/s100640050025 Calvello, M., Cuomo, S., & Ghasemi, P. (2017). The role of observations in the inverse analysis of landslide propagation. Computers and Geotechnics, 92, 11–21. Campos, L. M. De, Gamez, J. A., & Moral, S. (2001). Simplifying explanations in Bayesian belief networks. International Journal of Uncertainty, Puzziness and Knowledge-Based Systems, 9(4), 461–489. Caracol Radio. (2012). Nuevo dolor de cabeza generan obras en la Carrera 11 con 98. https://caracol.com.co/radio/2012/01/20/bogota/1327066020_609716.html Carper, K. L. (2000). Forensic Engineering. Taylor \& Francis. https://books.google.com.bo/books?id=gIu9BwAAQBAJ Chen, S. H., & Pollino, C. A. (2012). Good practice in Bayesian network modelling. Environmental Modelling & Software, 37, 134–145. https://doi.org/https://doi.org/10.1016/j.envsoft.2012.03.012 Chowdhury, R. N. (1987). Aspects of the Vajont slide. 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L. Sivakumar Babu (Eds.); pp. 535–548). Springer India. https://doi.org/10.1007/978-81-322-2377-1_35 Jeffreys, H. (1961). Theory of Probability (Third Edit). Clarendon Press. Jensen, F. V., & Nielsen, T. D. (2007). Bayesian Networks and Decision Graphs. In Information Science and Statistics. Springer, New York, NY. https://doi.org/https://doi.org/10.1007/978-0-387-68282-2 Jessep, R. A., de Mello, L. G., & Rao, V. V. S. (2016). Technical Shortcomings Causing Geotechnical Failures: Report of Task Force 10, TC 302 BT - Forensic Geotechnical Engineering (V. V. S. Rao & G. L. Sivakumar Babu (Eds.); pp. 267–295). Springer India. https://doi.org/10.1007/978-81-322-2377-1_19 Johnson, D. H. (1999). The Insignificance of Statistical Significance Testing. The Journal of Wildlife Management, 63(3), 763–772. https://doi.org/10.2307/3802789 Kadane, J. B., & Schum, D. A. (1998). A Probabilistic Analysis of the Sacco and Vanzetti Evidence. 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Reconocimiento 4.0 Internacionalhttp://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Colmenares Montañez, Julio Estebancc92ffe792a53c34a8258076fac18bbbGarcia Feria, William Mauricio9198fba6b157ebf608ec4709b8f77fefGENKI - Geotechnical Engineering Knowledge and InnovationGarcia-Feria, William Mauricio [0000-0002-4407-5579]Garcia, William MauricioGarcia-Feria, MauricioGarcia-Feria, Mauricio2023-10-09T15:41:28Z2023-10-09T15:41:28Z2023https://repositorio.unal.edu.co/handle/unal/84789Universidad Nacional de ColombiaRepositorio Institucional Universidad Nacional de Colombiahttps://repositorio.unal.edu.co/ilustraciones, diagramasRecent advances in engineering have increased the community’s expectation for civil engineering works to operate safely. Occasionally some of these works fail because of human errors or the unpredictable behavior of materials. Forensic engineering is the branch of forensic science in charge of investigating those engineering failures. Scientific methods used in forensic engineering guarantee that conclusions regarding the causes of an engineering failure come from reliable investigation processes. However, in the case of geotechnical failures, the inherent uncertainty of soil/rock materials, difficulties in evidence collection, and multiplicity of failure scenarios (hypotheses) pose a challenge in identifying the actual causes of failure. Therefore, conclusions about the causes of geotechnical failures sometimes seem arbitrary and biased because they are mainly based on expert judgment. Bayesian probabilistic tools can support decision-making about the causes of geotechnical failures. This thesis presents a Bayesian methodology for decision support in forensic geotechnical engineering based on two probabilistic techniques: Bayesian inference via posterior odds ratio and Bayesian Networks. The methodology compares probabilistically the hypotheses formulated as causes of failure and evaluates the influence of the amount of information (evidence) included in the analysis. Two benchmark problems and a case study were used to validate the applicability of the methodology. The results show that the Bayesian methodology identifies the most likely cause of a geotechnical failure, even when the amount of evidence is sparse. The use of the proposed methodology improves decision-making processes related to the causes of geotechnical failures. (Texto tomado de la fuente)Los recientes avances de la ingeniería han aumentado la expectativa de la comunidad de que las obras civiles funcionen con seguridad. Ocasionalmente, algunas de estas obras fallan debido a errores humanos o al comportamiento imprevisible de los materiales. La ingeniería forense es la rama de la ciencia forense encargada de investigar las fallas en ingeniería. Los métodos científicos utilizados por la ingeniería forense garantizan que las conclusiones sobre las causas de una falla provengan de procesos de investigación confiables. Sin embargo, en el caso de fallas geotécnicas, la incertidumbre inherente a los materiales de suelo y roca, las dificultades en la recolección de evidencia y la multiplicidad de escenarios de falla (hipótesis) suponen un reto para identificar las verdaderas causas de falla. En consecuencia, las conclusiones relacionadas con las causas de fallas geotécnicas algunas veces lucen arbitrarias y sesgadas porque se basan principalmente en el juicio de los expertos. Las herramientas probabilísticas bayesianas pueden apoyar la toma de decisiones sobre las causas de fallas geotécnicas. Esta tesis presenta una metodología bayesiana de apoyo a la toma de decisiones en ingeniería geotécnica forense utilizando dos técnicas probabilísticas: Inferencia bayesiana empleando las técnicas posterior odds ratio y Redes Bayesianas. La metodología compara probabilísticamente las hipótesis formuladas como causas de una falla y evalúa la influencia de la cantidad de información (evidencia) incluida en el análisis. Se presentan dos problemas de referencia y un caso de estudio para su validación. La metodología bayesiana identifica la causa más probable de la falla, incluso cuando la cantidad de evidencia es escasa. Además, su aplicación mejora la toma de decisiones relacionadas con las causas de fallas geotécnicas.DoctoradoDoctor en ingenieria civilGeotecnia y Riesgos Geoambientalesxix, 210 páginasapplication/pdfengUniversidad Nacional de ColombiaBogotá - Ingeniería - Doctorado en Ingeniería - Ingeniería CivilFacultad de IngenieríaBogotá, ColombiaUniversidad Nacional de Colombia - Sede Bogotá620 - Ingeniería y operaciones afines::624 - Ingeniería civilTeoría bayesiana de decisiones estadísticasDecisiones estadísticasBayesian statistical decision theoryStatistical decisionForensic geotechnical engineeringBayesian inferenceBayesian NetworksBayesian network methodology for decision support in forensic geotechnical engineeringMetodología de redes bayesianas para apoyar la toma de decisiones en ingeniería geotécnica forenseTrabajo de grado - Doctoradoinfo:eu-repo/semantics/doctoralThesisinfo:eu-repo/semantics/acceptedVersionhttp://purl.org/coar/resource_type/c_db06Texthttp://purl.org/redcol/resource_type/TDAllenby, G. M. (1990). Hypothesis Testing with Scanner Data: The Advantage of Bayesian Methods. Journal of Marketing Research, 27(4), 379–389. https://doi.org/10.1177/002224379002700401Alonso, E. E., Pinyol, N. M., & Puzrin, A. M. (2010). Geomechanics of failures. Advanced topics. In Geomechanics of Failures. Advanced Topics. https://doi.org/10.1007/978-90-481- 3538-7Alonso, E. E., Pinyol, N. P., & Fernández, P. (2016). Caisson Failure Induced by Wave Action BT - Forensic Geotechnical Engineering (V. V. S. Rao & G. L. Sivakumar Babu (Eds.); pp. 45– 93). Springer India. https://doi.org/10.1007/978-81-322-2377-1_4Antonucci, A. (2018). Reliable Discretisation of Deterministic Equations in Bayesian Networks. The Thirty-Second International Florida Artificial Intelligence Research Society Conference (FLAIRS-32), 453–457.ASCE. (2018). Guidelines for Failure Investigation. In R. S. Barrow, R. W. Anthony, K. J. Beasley, & S. M. 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Convocatoria 757MINCIENCIASInvestigadoresLICENSElicense.txtlicense.txttext/plain; charset=utf-85879https://repositorio.unal.edu.co/bitstream/unal/84789/1/license.txteb34b1cf90b7e1103fc9dfd26be24b4aMD51ORIGINALGarcia-Feria_Bayesian_Network_Forensic_Geotechnical_Engineering.pdfGarcia-Feria_Bayesian_Network_Forensic_Geotechnical_Engineering.pdfTesis de Doctorado en Ingeniería - Ingeniería Civilapplication/pdf9356255https://repositorio.unal.edu.co/bitstream/unal/84789/2/Garcia-Feria_Bayesian_Network_Forensic_Geotechnical_Engineering.pdf08fae190554f773f5cde3deb760db728MD52THUMBNAILGarcia-Feria_Bayesian_Network_Forensic_Geotechnical_Engineering.pdf.jpgGarcia-Feria_Bayesian_Network_Forensic_Geotechnical_Engineering.pdf.jpgGenerated Thumbnailimage/jpeg4808https://repositorio.unal.edu.co/bitstream/unal/84789/3/Garcia-Feria_Bayesian_Network_Forensic_Geotechnical_Engineering.pdf.jpg2f704809aedeb7fa8313557380185822MD53unal/84789oai:repositorio.unal.edu.co:unal/847892024-08-18 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