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.
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Showing 1 to 20 of 143 for “"model evaluation"”.
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Quantifying Uncertainty in Model Evaluation
As Machine Learning models have quickly evolved in the past decade, ways of measuring their potential haven’t. This proposal will pose that simple point estimate performance indicators are ill suited to describe models that exhibit inherent variability. Addressing classifier performance variability …
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Essays on Urban Climate Model Evaluation and Application
… policies. To that end, urban climate models are an invaluable tool for examining urban processes in more detail. However, their application in urban areas (particularly for planning problems) remains ad hoc and unsystematic. In fact, many cities in the economically developing world …
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Model evaluation for seasonal forecasting over southern Africa
… primary objective is to understand where global models show shortcomings in their simulations, and how this impacts on their seasonal forecast skill. It is proposed that the skill of a model in simulating natural climate variability is an appropriate metric for a model's potential skill in …
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The Unified Approach for Model Evaluation in Structural Equation Modeling
Practical fit indices have been widely used for model fit evaluation in Structural Equation Modeling. This dissertation discusses the properties of the fit indices including their influencing factors. These properties prevent researchers from deriving one-size-fit-all cutoffs for the fit indices. …
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Cluster-model evaluation of neutron cross selection for light-weight nuclei
Typescript (photocopy).
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A prototype parallel multi-FPGA accelerator for SPICE CMOS model evaluation
… exploit the inherent parallelism in the device model evaluation phase within the SPICE simulator. A code transformation flow which converts the high-level device model code to structural VHDL was also implemented. This flow showed that an automatic compiler system to design, map, and optimise …
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Bioaerosol Dispersal Across Scales: Regional Patterns, Field Study, and Model Evaluation
… dissertation uses Lagrangian stochastic (LS) models to simulate how these particles travel and deposit across scales relevant for cross-pollination, with applications to many types of biological aerosols. First, we map seasonal and regional patterns of windborne hemp pollen across the United …
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Ice Island Deterioration in the Canadian Arctic: Rates, Patterns and Model Evaluation
… Validation of operational surface ablation models was also carried out with in-situ microclimate measurements. The Canadian Ice Service iceberg model under-predicted surface ablation by 68%, while a more complete energy-balance model developed for ice islands improved output accuracy (7.5% …
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Subpopulation selection and debiased estimation for causal inference and predictive model evaluation
Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2026-12-01
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Toward better subseasonal-to-seasonal prediction: physics-oriented model evaluation and predictability of tropical cyclones
… remains a challenge for global numerical models. This is mostly because the sources of predictability on S2S timescales are not fully understood and/or not well represented in global models. My Ph.D. thesis research seeks to improve the model performance and the S2S prediction by 1) …
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Computational Software for Building Biochemical Reaction Network Models with Differential Equations
… physiology requires accurate mathematical models that depict the temporal dynamics of these chemical processes. Modelers build mathematical models of chemical processes primarily from systems of differential equations. Although developing new biological ideas is more of an art than a …
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Scalable Diskless Checkpointing for Large Parallel Systems
… projection, we have also developed an analytical model to investigate the performability of diskless checkpointing. Our model evaluation shows that the overhead of checkpoint/recovery is small on systems with thousands of nodes, and with appropriate partitioning of nodes, the user application can …
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Semiparametric Bayesian Approach using Weighted Dirichlet Process Mixture For Finance Statistical Models
… can be viewed as extension of DPM which relaxes model distribution assumptions. Meanwhile, WDPM requires to set weight functions and can cause extra computation burden. In this dissertation, we develop more efficient and exible WDPM approaches under three research topics. The first one is …
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PARASPICE: A parallel direct circuit simulator for shared-memory multiprocessors
… the three most compute-intensive modules: device model evaluation (LOAD), direct solution of sparse linear systems (SOLVE), and local truncation error estimation (TRUNC), which account for at least 95 percent of the total job time. Therefore, it is suitable for a wide range of shared-memory …
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Evaluation, Interpretation, and Maintenance of Machine Learning Models for IT Operations
… of large-scale systems and machine learning models to assist in managing system operations. While prior studies focus on innovative modeling techniques to improve the performance of AIOps models, how to smoothly transition AIOps solutions from development to production remains an …
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Comparative Analysis of Machine Learning Models for ERCOT Short Term Load Forecasting
… machine learning (ML) and deep learning (DL) models for short-term load forecasting (STLF) in the Electric Reliability Council of Texas (ERCOT) grid. A dual comparative approach is employed, evaluating models based on temporal features alone as well as in combination with actual and forecasted …
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CONTINENTAL SCALE DIAGNOSTIC EVALUATION OF MONTHLY WATER BALANCE MODELS FOR THE UNITED STATES
Water balance models are important for the characterization of hydrologic systems, to help understand regional scale dynamics, and to identify hydro-climatic trends and systematic biases in data. Because existing models have, to-date, only been tested on data sets of limited spatial …
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Application of data mining techniques to predict the performance of matured Vertical Flow Constructed Wetlands Systems treating urban wastewater
… to remove removal from wastewater. The overall evaluation of the system treatment performance was calculated using percentage removal efficiency. The results were recorded it was observed that all vertical flow constructed wetland filters had recorded high removal performance for the water …
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Dataset Interfaces: Diagnosing Model Failures Using Controllable Counterfactual Generation
… a major source of failure for machine learning models. However, evaluating model reliability under distribution shift can be challenging, especially since it may be difficult to acquire counterfactual examples that exhibit a specified shift. In this work, we introduce the notion of a dataset …
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