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Full-Text Articles in Physical Sciences and Mathematics
Developing Algorithms To Detect Incidents On Freeways From Loop Detector And Vehicle Re-Identification Data, Biraj Adhikari
Developing Algorithms To Detect Incidents On Freeways From Loop Detector And Vehicle Re-Identification Data, Biraj Adhikari
Civil & Environmental Engineering Theses & Dissertations
A new approach for testing incident detection algorithms has been developed and is presented in this thesis. Two new algorithms were developed and tested taking California #7, which is the most widely used algorithm to date, and SVM (Support Vector Machine), which is considered one of the best performing classifiers, as the baseline for comparisons. Algorithm #B in this study uses data from Vehicle Re-Identification whereas the other three algorithms (California #7, SVM and Algorithm #A) use data from a double loop detector for detection of an incident. A microscopic traffic simulator is used for modeling three types of incident …
The Messy Nuclear Landscape: Using Fuzzy Cognitive Mapping To Explore Plausible Nuclear Disarmament Scenarios, Ryan M. Nixon
The Messy Nuclear Landscape: Using Fuzzy Cognitive Mapping To Explore Plausible Nuclear Disarmament Scenarios, Ryan M. Nixon
Graduate Program in International Studies Theses & Dissertations
Nuclear weapons are seemingly permanent fixtures in international relations. Although nuclear abolitionists and actors within the Nonproliferation Treaty (NPT) and the International Atomic Energy Agency (IAEA) have taken significant steps towards designing a world without nuclear weapons, the longstanding realist logic that suggests nuclear disarmament is nonviable has born more fruit. On the other hand, some proponents of realism have suggested global nuclear disarmament is feasible, given that certain international instabilities are stabilized and that special care is taken during diplomatic negotiations. This presents an opportunity to test these predictions using fuzzy cognitive mapping, a computational modeling technique that identifies …
Latent Choice Models To Account For Misclassification Errors In Discrete Transportation Data, Lacramioara Elena Balan
Latent Choice Models To Account For Misclassification Errors In Discrete Transportation Data, Lacramioara Elena Balan
Civil & Environmental Engineering Theses & Dissertations
One of the most fundamental tasks when it comes to analyzing data using statistical methods is to understand the relationship between the explanatory variables and the outcome. Misclassification of explanatory variables is a common risk when using statistical modeling techniques. In this dissertation, we define ‘misclassification,’ as a response that is reported or recorded in the wrong category; for example, a variable is registered as a one when it should have the value zero. Misclassification can easily happen in any data; for example, in an interview setting where the respondent misunderstands the question or the interviewer checks the wrong box. …