Examinando por Materia "Risk assessment"
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Ítem Administración de riesgos empresariales en Colombia, México y Argentina(Editorial Eafit, 2017) Albanese, Diana; Blanco Mesa, Fabio Raúl; Briozzo, Anahí; Carrizo, Mariana; Cifuentes Valenzuela, Jorge; Cruz Ramírez, Dorie; Díaz Restrepo, Carlos Andrés; Godoy Rodríguez, Martha Rocío; Gutiérrez Bernal, Luis Gabriel; Londoño Pineda, Nelson; Mancilla-Rendón, Ma. Enriqueta; Marín, Yudi; Martínez Garro, Daniela; Mora Álvarez, José Manuel; Oviedo, Elizabeth; Pérez Castañeda, Suly Sendi; Quintero, Dora P.; Salazar Yépes, Gloria Stella; Sauza Ávila, Beatríz; Villanueva, Eduart; Vahos Correa, Juan Esteban; Mejía Quijano, Rubi Consuelo; Nuñéz-Patiño, María Antonia; Martins, Izaías; Universidad EAFIT. Departamento de Administración; Información y GestiónAdministración de Riesgos Empresariales en Colombia, México y Argentina da a conocer un completo diagnóstico del desarrollo de la administración de riesgos en grandes empresas privadas de los tres países participantes, en el cual se evidencia una importante evolución de esta disciplina en el marco del gobierno y la cultura del riesgo, las prácticas y herramientas, la comunicación y consulta, entre otros elementos estudiados -- Con esto se ratifica el valor de esta disciplina para contribuir a la responsabilidad social empresarial, y el impacto en los resultados financieros y la sostenibilidad de las empresasÍtem Advances and trends of head-up and head-down display systems in automobiles(SPIE-INT SOC OPTICAL ENGINEERING, 2014-01-01) Alejandro Betancur, J.; Osorio-Gomez, Gilberto; Externo - Escuela - IngenieríaCurrently, in the automotive industry the interaction between drivers and Augmented Reality (AR) systems is a subject of analysis, especially the identification of advantages and risks that this kind of interaction represents. Consequently, this paper attempts to put in evidence the potential applications of Head-Up (Display (HUD) and Head-Down Display (HDD) systems in automotive vehicles, showing applications and trends under study. In general, automotive advances related to AR devices suggest the partial integration of the HUD and HDD in automobiles; however, the right way to do it is still a moot point. © 2014 SPIE.Ítem Advances and trends of head-up and head-down display systems in automobiles(SPIE-INT SOC OPTICAL ENGINEERING, 2014-01-01) Alejandro Betancur, J.; Osorio-Gomez, Gilberto; Externo - Escuela - Ingeniería; Alejandro Betancur, J.; Osorio-Gomez, Gilberto; Externo - Escuela - Ingeniería; Universidad EAFIT. Departamento de Ingeniería Mecánica; Mecánica AplicadaCurrently, in the automotive industry the interaction between drivers and Augmented Reality (AR) systems is a subject of analysis, especially the identification of advantages and risks that this kind of interaction represents. Consequently, this paper attempts to put in evidence the potential applications of Head-Up (Display (HUD) and Head-Down Display (HDD) systems in automotive vehicles, showing applications and trends under study. In general, automotive advances related to AR devices suggest the partial integration of the HUD and HDD in automobiles; however, the right way to do it is still a moot point. © 2014 SPIE.Ítem Aplicación de árboles de decisión para la valoración de compañías de minería aluvial(Universidad EAFIT, 2013) Echavarría Echeverri, María Adelaida; Rodas Vélez, Camilo; Urrego Moreno, Lina María; Hernández Bonnet, AlvaroÍtem Automatic detection of building typology using deep learning methods on street level images(PERGAMON-ELSEVIER SCIENCE LTD, 2020-03-20) Duque, J.; Gonzalez, D.; Rueda Plata, Diego; Acevedo, A.; Ramos, R.; Betancourt, A.; García, S.; Mecánica AplicadaAn exposure model is a key component for assessing potential human and economic losses from natural disasters. An exposure model consists of a spatially disaggregated description of the infrastructure and population of a region under study. Depending on the size of the settlement area, developing such models can be a costly and time-consuming task. In this paper we use a manually annotated dataset consisting of approximately 10,000 photos acquired at street level in the urban area of Medellín to explore the potential for using a convolutional neural network (CNN) to automatically detect building materials and types of lateral-load resisting systems, which are attributes that define a building's structural typology (which is a key issue in exposure models for seismic risk assessment). The results of the developed model achieved a precision of 93% and a recall of 95% when identifying nonductile buildings, which are the buildings most likely to be damaged in an earthquake. Identifying fine-grained material typology is more difficult, because many visual clues are physically hidden, but our model matches expert level performances, achieving a recall of 85% and accuracy scores ranging from 60% to 82% on the three most common building typologies, which account for 91% of the total building population in Medellín. Overall, this study shows that a CNN can make a substantial contribution to developing cost-effective exposure models. © 2020 Elsevier LtdÍtem Automatic detection of building typology using deep learning methods on street level images(PERGAMON-ELSEVIER SCIENCE LTD, 2020-03-20) Duque, J.; Gonzalez, D.; Rueda Plata, Diego; Acevedo, A.; Ramos, R.; Betancourt, A.; García, S.; Universidad EAFIT. Departamento de Economía y Finanzas; Research in Spatial Economics (RISE)An exposure model is a key component for assessing potential human and economic losses from natural disasters. An exposure model consists of a spatially disaggregated description of the infrastructure and population of a region under study. Depending on the size of the settlement area, developing such models can be a costly and time-consuming task. In this paper we use a manually annotated dataset consisting of approximately 10,000 photos acquired at street level in the urban area of Medellín to explore the potential for using a convolutional neural network (CNN) to automatically detect building materials and types of lateral-load resisting systems, which are attributes that define a building's structural typology (which is a key issue in exposure models for seismic risk assessment). The results of the developed model achieved a precision of 93% and a recall of 95% when identifying nonductile buildings, which are the buildings most likely to be damaged in an earthquake. Identifying fine-grained material typology is more difficult, because many visual clues are physically hidden, but our model matches expert level performances, achieving a recall of 85% and accuracy scores ranging from 60% to 82% on the three most common building typologies, which account for 91% of the total building population in Medellín. Overall, this study shows that a CNN can make a substantial contribution to developing cost-effective exposure models. © 2020 Elsevier LtdÍtem Automatic detection of building typology using deep learning methods on street level images(PERGAMON-ELSEVIER SCIENCE LTD, 2020-03-20) Duque, J.; Gonzalez, D.; Rueda Plata, Diego; Acevedo, A.; Ramos, R.; Betancourt, A.; García, S.; Duque, J.; Gonzalez, D.; Rueda Plata, Diego; Acevedo, A.; Ramos, R.; Betancourt, A.; García, S.; Universidad EAFIT. Departamento de Ingeniería de Producción; Materiales de IngenieríaAn exposure model is a key component for assessing potential human and economic losses from natural disasters. An exposure model consists of a spatially disaggregated description of the infrastructure and population of a region under study. Depending on the size of the settlement area, developing such models can be a costly and time-consuming task. In this paper we use a manually annotated dataset consisting of approximately 10,000 photos acquired at street level in the urban area of Medellín to explore the potential for using a convolutional neural network (CNN) to automatically detect building materials and types of lateral-load resisting systems, which are attributes that define a building's structural typology (which is a key issue in exposure models for seismic risk assessment). The results of the developed model achieved a precision of 93% and a recall of 95% when identifying nonductile buildings, which are the buildings most likely to be damaged in an earthquake. Identifying fine-grained material typology is more difficult, because many visual clues are physically hidden, but our model matches expert level performances, achieving a recall of 85% and accuracy scores ranging from 60% to 82% on the three most common building typologies, which account for 91% of the total building population in Medellín. Overall, this study shows that a CNN can make a substantial contribution to developing cost-effective exposure models. © 2020 Elsevier LtdÍtem Comparación de metodologías para la zonificación del riesgo de detalle, para los Barrios Pinares de Oriente, Esfuerzos de Paz y San Antonio en el municipio de Medellín(Universidad EAFIT, 2018) Giraldo Zuluaga, Juan Esteban; Gamboa Ramírez, Marco FidelÍtem Comparación entre el método tradicional y algunos basados en inteligencia artificial para el estudio del riesgo crediticio en instituciones financieras colombianas(Universidad EAFIT, 2018) Arango Correa, Diana Marcela; Colmenares Colmenares, Laura Juliana; Rave Contreras, Isabel Cristina; Martínez Negrete, Milton AlfonsoArtificial intelligence models are an open problem for application in various fields of science and search of variable relationships especially when the distribution of events doesn’t depend on a linear function; through this work we want to compare the traditional method most used for credit behavior monitoring with advanced models of artificial intelligence -- The guides that exist in Colombia for management of credit risk are given by the Financial Superintendence of Colombia, international standards such as Basel II, Basel III and Solvency are based on the logistic regression and the discriminant analysis, models used by financial institutions in Colombia to measure credit behavior, thus we carried out an investigation to explore the utility of new models -- This paper addresses one of the traditional methods used in financial institutions, that is, logistic regression, and compares it with alternative methods such as neural networks and random forests -- From the literature review and using a database provided by a banking entity, the dependent variables and the response variable are selected, the logistic regression models, random forests and neural networks are calibrated in the Microsoft Azure Machine Learning application and they are compared to each other with indicators of precision and accuracy such as ROC (from receiver operating characteristic) curve and confusion matrix, obtaining for the models of artificial intelligence, results as good as the traditional one; so they can be used by the financial sector as alternate and / or complementary methods in the analysis of credit riskÍtem El control de pérdidas en materiales de agregados y mezclas en obras de infraestructura(Universidad EAFIT, 2017) Agudelo Galeano, Sebastián; González Mazo, José Daniel; N/AIn Colombia, the vast network of road infrastructure is old and inadequate, resulting in low average speed, higher vehicle maintenance cost, and excessive fuel cost which together have become a major hindrance to the national economic development of Colombia -- More than a decade ago, the national governments develop a national plan to improve the quality of roads in Colombia, thereby reducing the economic and social cost associated with poorly developed road infrastructure. Within the plan, construction resource management practices as defined in project contracts including subcontracting, aggregate resource - material, mixture and fuel - use & management were identified -- In this paper, these risk management issues associated with the resource management are addressed, and the current regulations that governs these issues will be reviewed -- Using economic and accounting concept of cost, project management practices will be examined to identity potential and real wastage of construction resources -- In addition, utilizing concepts of risk management, new controls and methodologies will be discussed and proposed to minimize the loss & wastage of construction resourcesÍtem Desarrollo de una propuesta de la gestión de riesgos estratégicos según el método Risicar en una Pyme del sector metalmecánico(2018) Castañeda Gil, Jorge Enrique; Núñez Patiño, María Antonia; Giraldo Hernández, Gina MaríaFor the companies it is much more relevant identify, weigh and doing risk management, because this risks can put in jeopardy the business sustainability, and more when we are dealing with Pymes -- That is why this work aims to identify and weigh the risks to the company Metalmecánica S. A. S. located in the city of Pereira, this company belongs to the metal mechanic sector -- For this paper the methodology being use is qualitative, exploratory research will be used in order to collect the necessary information of the main activities and processes of the companyÍtem Desprendimiento de rocas en laderas: una guía para la evaluación del riesgo en vías(Universidad EAFIT, 2014) Arango Vélez, Ismael Fernando; Echeverri Ramírez, Gloria ElenaEn este trabajo se presenta una metodología y los lineamientos para evaluar el riesgo en vías por desprendimiento de rocas desde las laderas -- Esta guía puede ser utilizada en las diferentes etapas de un proyecto vial como diseño, construcción, operación y mantenimiento -- El proceso consta de varias fases las cuales se describen detalladamente para facilitar su aplicación -- Estas fases incluyen la clasificación preliminar con base en el diseño geométrico de la vía y la unidad morfogeológica; la obtención de parámetros estructurales del macizo rocoso y datos geotécnicos requeridos para el análisis; la modelación considerando la trayectoria del bloque desprendido y la evaluación con métodos observacionales; la determinación del grado de amenaza y la evaluación del riesgo -- Todas las etapas indicadas se ilustran con el estudio de un caso localÍtem Development of a fragility model for the residential building stock in South America(EARTHQUAKE ENGINEERING RESEARCH INST, 2017-05-01) Villar-Vega, Mabe; Silva, Vitor; Crowley, Helen; Yepes, Catalina; Tarque, Nicola; Acevedo, Ana Beatriz; Hube, Matias A.; Gustavo, Coronel D.; Maria, Hernan Santa; Mecánica AplicadaSouth America-in particular, the Andean countries-are exposed to high levels of seismic hazard, which, when combined with the elevated concentration of population and properties, has led to an alarming potential for human and economic losses. Although several fragility models have been developed in recent decades for South America, and occasionally used in probabilistic risk analysis, these models have been developed using distinct methodologies and assumptions, which renders any direct comparison of the results across countries questionable, and thus application at a regional level unreliable. This publication aims at obtaining a uniform fragility model for the most representative building classes in the Andean region, for large-scale risk analysis. To this end, sets of single-degree-of-freedom oscillators were created and subjected to a series of ground motion records using nonlinear time history analyses, and the resulting damage distributions were used to derive sets of fragility functions. © 2017, Earthquake Engineering Research Institute.Ítem Development of a fragility model for the residential building stock in South America(EARTHQUAKE ENGINEERING RESEARCH INST, 2017-05-01) Villar-Vega, Mabe; Silva, Vitor; Crowley, Helen; Yepes, Catalina; Tarque, Nicola; Acevedo, Ana Beatriz; Hube, Matias A.; Gustavo, Coronel D.; Maria, Hernan Santa; Villar-Vega, Mabe; Silva, Vitor; Crowley, Helen; Yepes, Catalina; Tarque, Nicola; Acevedo, Ana Beatriz; Hube, Matias A.; Gustavo, Coronel D.; Maria, Hernan Santa; Universidad EAFIT. Departamento de Ingeniería de Producción; Materiales de IngenieríaSouth America-in particular, the Andean countries-are exposed to high levels of seismic hazard, which, when combined with the elevated concentration of population and properties, has led to an alarming potential for human and economic losses. Although several fragility models have been developed in recent decades for South America, and occasionally used in probabilistic risk analysis, these models have been developed using distinct methodologies and assumptions, which renders any direct comparison of the results across countries questionable, and thus application at a regional level unreliable. This publication aims at obtaining a uniform fragility model for the most representative building classes in the Andean region, for large-scale risk analysis. To this end, sets of single-degree-of-freedom oscillators were created and subjected to a series of ground motion records using nonlinear time history analyses, and the resulting damage distributions were used to derive sets of fragility functions. © 2017, Earthquake Engineering Research Institute.Ítem Development of a global seismic risk model(EARTHQUAKE ENGINEERING RESEARCH INST, 2020-02-02) Vitor Silva; Desmond Amo-Oduro; Alejandro Calderon; Catarina Costa; Jamal Dabbeek; Venetia Despotaki; Luis Martins; Marco Pagani; Anirudh Rao; Michele Simionato; Daniele Viganò; Catalina Yepes-Estrada; Ana Acevedo; Helen Crowley; Nick Horspool; Kishor Jaiswal; Murray Journeay; Massimiliano Pittore; Mecánica AplicadaSince 2015, the Global Earthquake Model (GEM) Foundation and its partners have been supporting regional programs and bilateral collaborations to develop an open global earthquake risk model. These efforts led to the development of a repository of probabilistic seismic hazard models, a global exposure dataset comprising structural and occupancy information regarding the residential, commercial and industrial buildings, and a comprehensive set of fragility and vulnerability functions for the most common building classes. These components were used to estimate probabilistic earthquake risk globally using the OpenQuake-engine, an open-source software for seismic hazard and risk analysis. This model allows estimating a number of risk metrics such as annualized average losses or aggregated losses for particular return periods, which are fundamental to the development and implementation of earthquake risk mitigation measures. © The Author(s) 2020.Ítem Development of a global seismic risk model(EARTHQUAKE ENGINEERING RESEARCH INST, 2020-02-02) Global Earthquake Model Foundation; Global Earthquake Model Foundation; Global Earthquake Model Foundation; Global Earthquake Model Foundation; Global Earthquake Model Foundation; Global Earthquake Model Foundation; Global Earthquake Model Foundation; Global Earthquake Model Foundation; Global Earthquake Model Foundation; Global Earthquake Model Foundation; Global Earthquake Model Foundation; Global Earthquake Model Foundation; Acevedo, A.; EUCENTRE; GNS Science; US Geological Survey; Natural Resources of Canada; GFZ Potsdam; Global Earthquake Model Foundation; Global Earthquake Model Foundation; Global Earthquake Model Foundation; Global Earthquake Model Foundation; Global Earthquake Model Foundation; Global Earthquake Model Foundation; Global Earthquake Model Foundation; Global Earthquake Model Foundation; Global Earthquake Model Foundation; Global Earthquake Model Foundation; Global Earthquake Model Foundation; Global Earthquake Model Foundation; Acevedo, A.; EUCENTRE; GNS Science; US Geological Survey; Natural Resources of Canada; GFZ Potsdam; Universidad EAFIT. Departamento de Ingeniería de Producción; Materiales de IngenieríaSince 2015, the Global Earthquake Model (GEM) Foundation and its partners have been supporting regional programs and bilateral collaborations to develop an open global earthquake risk model. These efforts led to the development of a repository of probabilistic seismic hazard models, a global exposure dataset comprising structural and occupancy information regarding the residential, commercial and industrial buildings, and a comprehensive set of fragility and vulnerability functions for the most common building classes. These components were used to estimate probabilistic earthquake risk globally using the OpenQuake-engine, an open-source software for seismic hazard and risk analysis. This model allows estimating a number of risk metrics such as annualized average losses or aggregated losses for particular return periods, which are fundamental to the development and implementation of earthquake risk mitigation measures. © The Author(s) 2020.Ítem Development of structural debris flow fragility curves (debris flow buildings resistance) using momentum flux rate as a hazard parameter(Elsevier B.V., 2018-05-18) Prieto, Jorge Alonso; Journeay, Murray; Acevedo A.B.; Arbelaez, Juan; Ulmi, Malaika; Prieto, Jorge Alonso; Journeay, Murray; Acevedo A.B.; Arbelaez, Juan; Ulmi, Malaika; Universidad EAFIT. Departamento de Ingeniería de Producción; Materiales de IngenieríaSocietal risks associated with debris flow hazards are significant and likely to escalate due to global population growth trends and the compounding effects of climate change. Quantitative risk assessment methods (QRA) provide a means of anticipating the likely impacts and consequences of settlement in areas susceptible to landslide activity and are increasingly being used to inform land use decisions that seek to increase disaster resilience through mitigation and/or adaptation. Current QRA methods for debris flow hazards are based primarily on empirical vulnerability functions that relate hazard intensity (depth, velocity, etc.) to expected levels of loss for a given asset of concern, i.e. most of current methods are dedicated to loss-intensity relations. Though grounded in observed cause-effect relationships, empirical vulnerability functions are not designed to predict the capacity of a building to withstand the physical impacts of a debris flow event, or the related uncertainties associated with modelling building performance as a function of variable debris flow parameters. This paper describes a methodology for developing functions that relate hazard intensity to probability of structural damage, i.e., fragility functions, rather than vulnerability functions, based on the combined hydrodynamic forces of a debris flow event (hazard level) and the inherent structural resistance of building typologies that are common in rural mountainous settings (building performance). Hazard level includes a hydrodynamic force variable (FDF), which accounts for the combined effects of debris flow depth and velocity, i.e. momentum flux (hv2), material density (?) and related flow characteristics including drag (Cd) and impact coefficient (Kd). Building performance is measured in terms of yield strength (Ay), ultimate lateral capacity (AU) and weight to breadth ratios (W/B) defined for a portfolio building types that are common in mountain settlements. Collectively, these model parameters are combined using probabilistic methods to produce building-specific fragility functions that describe the probability of reaching or exceeding successive thresholds of structural damage over a range of hazard intensity values, expressed in terms of momentum flux. Validation of the proposed fragility model is based on a comparison between model outputs and observed cause-effect relationships for recent debris flow events in South Korea and in Colombia. Debris flow impact momentum fluxes, capable of resulting in complete damage to unreinforced masonry buildings (URM) in those regions are estimated to be on the order of 24 m3/s2, consistent with field-based observations. Results of our study offer additional capabilities for assessing risks associated with urban growth and development in areas exposed to debris flow hazards. © 2018 Elsevier B.V.Ítem Development of structural debris flow fragility curves (debris flow buildings resistance) using momentum flux rate as a hazard parameter(Elsevier B.V., 2018-05-18) Prieto, Jorge Alonso; Journeay, Murray; Acevedo A.B.; Arbelaez, Juan; Ulmi, Malaika; Mecánica AplicadaSocietal risks associated with debris flow hazards are significant and likely to escalate due to global population growth trends and the compounding effects of climate change. Quantitative risk assessment methods (QRA) provide a means of anticipating the likely impacts and consequences of settlement in areas susceptible to landslide activity and are increasingly being used to inform land use decisions that seek to increase disaster resilience through mitigation and/or adaptation. Current QRA methods for debris flow hazards are based primarily on empirical vulnerability functions that relate hazard intensity (depth, velocity, etc.) to expected levels of loss for a given asset of concern, i.e. most of current methods are dedicated to loss-intensity relations. Though grounded in observed cause-effect relationships, empirical vulnerability functions are not designed to predict the capacity of a building to withstand the physical impacts of a debris flow event, or the related uncertainties associated with modelling building performance as a function of variable debris flow parameters. This paper describes a methodology for developing functions that relate hazard intensity to probability of structural damage, i.e., fragility functions, rather than vulnerability functions, based on the combined hydrodynamic forces of a debris flow event (hazard level) and the inherent structural resistance of building typologies that are common in rural mountainous settings (building performance). Hazard level includes a hydrodynamic force variable (FDF), which accounts for the combined effects of debris flow depth and velocity, i.e. momentum flux (hv2), material density (?) and related flow characteristics including drag (Cd) and impact coefficient (Kd). Building performance is measured in terms of yield strength (Ay), ultimate lateral capacity (AU) and weight to breadth ratios (W/B) defined for a portfolio building types that are common in mountain settlements. Collectively, these model parameters are combined using probabilistic methods to produce building-specific fragility functions that describe the probability of reaching or exceeding successive thresholds of structural damage over a range of hazard intensity values, expressed in terms of momentum flux. Validation of the proposed fragility model is based on a comparison between model outputs and observed cause-effect relationships for recent debris flow events in South Korea and in Colombia. Debris flow impact momentum fluxes, capable of resulting in complete damage to unreinforced masonry buildings (URM) in those regions are estimated to be on the order of 24 m3/s2, consistent with field-based observations. Results of our study offer additional capabilities for assessing risks associated with urban growth and development in areas exposed to debris flow hazards. © 2018 Elsevier B.V.Ítem Diseño e implementación de la estructura de riesgos para el proceso de inversión en una entidad sin ánimo de lucro: Universidad La Gran Colombia, seccional Armenia(Universidad EAFIT, 2014) Castaño Brito, Tatiana; Cárdenas Espinosa, Sandra Melissa; Torres Oke, SebastiánEn este trabajo se presenta un proceso de inversión para instituciones sin ánimo de lucro en el cual se diseña e implementa la estructura de riesgos, partiendo de la definición del perfil de riesgo del inversionista, identificando los excedentes reales susceptibles de ser invertidos para luego analizar las diferentes opciones que ofrece el mercado según la rentabilidad, para esto se utilizarán diferentes métodos a partir de una estructura de riesgos para así determinar la estrategia que más se acomode al perfil del inversionista -- El análisis se realiza tomando como marco de referencia la Universidad La Gran Colombia seccional Armenia, institución educativa de carácter privado cuyos excedentes se han invertido en entidades que ofrecen el mínimo riesgo -- Se estudiarán diferentes alternativas de inversión que incluyan entre otras Carteras colectivas, Multifondos, TES y títulos de renta variable, lo cual abrirá más el panorama de portafolios y permitirá tener una amplia gama de opciones a estudiar para luego entrar a definir cuál de ellas, son las más recomendadas para la institución en estudio, y así escoger la que cumpla con los requisitos establecidos por los estamentos de la Universidad, quienes finalmente decidirán si se invierte en el portafolio recomendado, también pueden encontrar más viable asumir un poco más de riesgo para que la inversión genere una rentabilidad mayor, o como última opción, decidir dejar la recursos en las entidades en las cuales los han estado invirtiendoÍtem Un estado del arte del análisis cualitativo y cuantitativo de riesgos en proyectos(Universidad EAFIT, 2016) Ángel Tamayo, Daniel; Hincapié Mejía, Marcela; Gómez Salazar, Elkin ArcesioEl continuo desarrollo en la gestión de riesgos se debe en parte a la gran cantidad de proyectos que se han realizado en diferentes ámbitos, con diferentes alcances y magnitudes -- Las metodologías cualitativas y cuantitativas de análisis de riesgos encontradas y expuestas en el marco de este trabajo han sido, en medida alguna, la guía para llegar a los métodos y herramientas que controlan y mitigan el impacto de la materialización de los riesgos, e igualmente han permitido el desarrollo de proyectos de una forma más versátil y eficaz -- El objetivo del presente trabajo es elaborar un estado del arte del análisis cualitativo y cuantitativo de riesgos en proyectos que incluye desarrollos, enfoques, métodos y herramientas -- Este trabajo fue realizado mediante una búsqueda de documentos académicos científicos en diferentes bases de datos, donde se encontraron veintiocho métodos cualitativos y once métodos cuantitativos que hoy en día son de gran importancia y ayuda para la gestión de riesgos, dependiendo de la etapa en la que esta se encuentre
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