Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
Results
Showing 1 to 20 of 33 for “"Risk Modeling"”.
-
Optimal Driver Risk Modeling
… considerable research on predicting driver risk and evaluating the impact of risk factors. Driver risk modeling is challenging due to the rarity of motor vehicle crashes and heterogeneity in individual driver risk. Statistical modeling and analysis of such driver data are often associated …
-
Risk-modeling tools for designing resilient micro energy grids
… matrix. In addition, it proposes two advanced risk-modeling approaches, namely fault tree and layer of resilience analysis (LORA), for risk and resilience analysis of MEG. Selected independent resilience layers (IRLs) were proposed to achieve a resilient MEG by increasing safety integrity level …
-
Time-Based Collision Risk Modeling for Air Traffic Management
… accompanied by a corresponding increase in the risk of collision, and in response to a growing number of incidents and accidents involving collisions between aircraft, governments worldwide have developed air traffic control systems and procedures to mitigate this risk. The objective of any …
-
Credit Risk Modeling and Analysis Using Copula Method and Changepoint Approach to Survival Data
… t Copula as the main tools to model the credit risk in securitizations and re-securitizations. The second part proposes a statistical procedure to identify changepoints in Cox model of survival data. The recent 2007-2009 financial crisis has been regarded as the worst financial crisis since the …
-
Flood risk modeling and impact assessment using google earth engine in Mpumalanga province, South Africa
… real-time monitoring systems and comprehensive risk assessment frameworks. This study aimed at addressing these challenges by developing an integrated spatial explicit flood risk assessment and monitoring framework using Google Earth Engine (GEE) cloud computing platform and multi-source spatial …
-
Machine Learning Based Flood Risk Modeling Using Features from Satellite, Socioeconomic, Geographic, and Building Data
… urban planners to have a low-cost and efficient modeling tool that can determine the flood risk at a granular level such as the census tract. Boston is one such coastal urban city that will experience an increase in flooding. Since each census tract in Boston is unique and varies in population …
-
Structural credit risk modeling using Merton model and its default probability: A case study of commercial banks in Namibia
… The primary objective is to assess the credit risk position in the light of the Merton Structural credit Risk Model. The financial statements of these banks are analysed, specifically the balance sheets and statements of income, to extract relevant information for the computation of various …
-
Towards Risk-Informed Development: Improving Political Disaster Risk Modeling in the Nile Basin Region Using Big Data and Machine Learning
… of this dissertation is to analyze disaster risk components and how they impact intrastate and interstate conditions in the context of resilient development. There are two main factors that affect disaster risk: exposure to specific natural hazards and vulnerability of a given region, …
-
Modeling Extreme Heat Risk in Urban Areas Using Computer Vision and Data Analysis
… created from human activities. As a result, heat risk modeling aims to reduce heat risk for vulnerable communities by assisting urban planners and policymakers in efficiently and effectively identifying regions within cities that may need more heat adaptation amenities. However, current heat risk …
-
Learning risk models for pancreatic cancer from electronic health records
… subtle, which underscores the need for better risk modeling to predict a patient's chance of pancreatic cancer well before it would usually be diagnosed. We propose a series of novel models that apply standard machine learning techniques to Electronic Health Records (EHRs) to predict risk of …
-
Discrete Particle Dynamics Models: Computational Aspects And Applications
… as, pedestrian particles in pedestrian movement modeling and molecules in material science modeling. These dynamic modeling approaches share a commonality in computational approach where a series of ordinary differential equations are solved for the particle’s motion and equilibrium under active …
-
Delinquency and default in ARMS: The effects of protected equity
… borrower equity in controlling mortgage risk. Simultaneously, we postulate mortgage delinquency as a necessary decision before the default decision such that motivations for delinquency exert significant influences on subsequent motivations for default. We find that increasing the use of …
-
Explaining machine learning predictions : rationales and effective modifications
… techniques traditionally used in credit risk modeling like logistic regression. However, deep learning models operate as black-boxes, which can limit their use and impact. Regulation mandates that a lender must be able to disclose up to four factors that adversely affected a rejected …
-
The Interaction of Policy, Credit Demand and Credit Supply in Banking System
… impact banks to make major changes within credit risk modeling, risk tolerance and capital management. Therefore, the objective of this study is to assess CECL’s treatment effect on bank’s lending strategy and risk profile management. My main model is a difference-in-difference model to study the …
-
Representation Learning Based Causal Inference in Observational Studies
… generative causal estimation, and invariant risk modeling, this dissertation establishes a causal framework that balances the covariate distribution in latent representation space to yield individualized estimations, and further contributes novel perspectives on causal effect estimation based …
-
Understanding political pressures To shutdown nuclear power plants in the United States and South Korea
… from groups that do not trust the typical risk and safety assessment studies used to justify license renewals; 2) nuclear license renewal decisions are particularly prone to conflict if stakeholders are not involved early enough, and if they perceive that their concerns are repeatedly …
-
Ethical Analytics: A Framework for a Practically-Oriented Sub-Discipline of AI Ethics
… for consumers (and lenders) in credit risk modeling, leading to the enumeration of 3 minimum requirements that explanations should meet in order to satisfy both regulatory and ethical considerations of transparency in the United States socio-historical and legislative context. It is …
-
Transportation system modeling and applications in earthquake engineering
… consequences. Therefore, understanding and modeling the disastrous impact on the transportation infrastructures and the corresponding changes of travel patterns under extreme events are vital for stakeholders, emergency managers, and government agencies to mitigate, prepare for, respond to, …
-
The Use of Geographic Information Systems and Ecological Niche Modeling to Map Transmission Risk for Visceral Leishmaniasis in Bahia, Brazil
… scale to define the role of these factors in risk area identification. At the statewide scale, the models were developed for Bahia state and data on vector occurrence was added to the analysis. Three environment structural indices were evaluated in addition to the environmental variables …
Page 1 of 2