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 171 for “"Neural network models"”.
-
Neural Network Models for Generating Synthetic Flight Data
… for data augmentation. In this thesis, several neural network architectures were investigated as methods of generating synthetic flight data that is consistent with the aircraft dynamics.</p>
-
Polarization-based underwater geolocalization with neural network models
Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2024-03-01 without embargo terms
-
Lipreading with convolutional and recurrent neural network models
… by a talking head, given only the video using neural network classification models. Two neural network architectures are developed and tested on the AVICAR dataset, including one convolutional neural network (CNN) model with fully connected classification layer, and one recurrent neural network …
-
Deep neural network models for image classification and regression
… Furthermore, the performance of deep learning models has a strong dependency on the way in which these latter are designed/tailored to the problem at hand. This, thereby, raises not only precision concerns but also processing overheads. The success and applicability of a deep learning system …
-
Neural network models for zebra finch song production and reinforcement learning
Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2001.
-
Exploring the landscape of backdoor attacks on deep neural network models
Deep neural networks have recently been demonstrated to be vulnerable to backdoor attacks. Specifically, by introducing a small set of training inputs, an adversary is able to plant a backdoor in the trained model that enables them to fully control the model's behavior during inference. In this …
-
Mosaic solutions and spatial entropy for a class of neural network models
Includes bibliographical references (pages 42-44).
-
TESTING THE UTILITY OF NEURAL NETWORK MODELS TO PREDICT HISTORY OF ARREST IN BATTERERS
… recidivism. Previous studies have used linear models that rely on variables that have been linked to past history of intimate partner violence (IPV) based on men’s report only. The current study compares the non-linear neural network model to traditional linear models in predicting a history of …
-
Beans to Bytes: Grey-Box Nonlinear System Identification Using Hybrid Physics-Neural Network Models
The advancement of neural networks in the last several years has yielded some astonishing results. However, the applicability to system identification and modelling dynamical systems still has a great amount of room for exploration. This thesis reviews different neural network architectures and …
-
Combined bottom-hole pressure calculation procedure using multiphase correlations and artificial neural network models, A
Artificial neural network (ANN) techniques have been adopted to predict bottom-hole pressures and have proved to have better, or at a minimum equivalent prediction performance than conventional prediction methods such as multiphase correlations and mechanistic modeling. With the applied design, the …
-
Predicting hybrid vehicle fuel economy and emissions with neural network models trained with real world data
Physics-based hybrid vehicle simulation models for fuel economy (FE) exist but are computationally and financially expensive. These models simulate aspects of real-world drive cycles that include the driving environment, thermal management, driver input, and powertrain component behavior. In this …
-
Applying Neural Network Models to Predict Recurrent Maltreatment in Child Welfare Cases with Static and Dynamic Risk Factors
… welfare has a long tradition of being based on models that assume the likelihood of recurrent maltreatment is a linear function of its various predictors: Gambrill & Shlonsky, 2000). Despite repeated testing of many child, parent, family, maltreatment incident, and service delivery variables, no …
-
Use of artificial neural network models to derive particle size distributions and their moments from chord length distributions
… strategy to be used is dependent on kinetic models of the process. These are in turn dependent on the zeroth to fifth moments of the particle size distribution and the supersaturation levels of the solution. In order to apply advanced control to a process, continuous monitoring of the process …
-
Artificial neural network models utilize chamber-specific predictors of cardiac fibrosis in ovariectomized and aortic-banded Yucatan mini-swine
… and used as input variables in an artificial neural network model (ANN). This model will identify best predictors for experimental group status i.e., the combination of the loss of female sex hormone and/or pressure overload status, as an indication for the biological roles they play in the …
-
Comparing Traditional Statistical Models with Neural Network Models: The Case of the Relation of Human Performance Factors to the Outcomes of Military Combat
<p>Statistics and neural networks are analytical methods used to learn about observed experience. Both the statistician and neural network researcher develop and analyze data sets, draw relevant conclusions, and validate the conclusions. They also share in the challenge of creating accurate …
-
An optimizing compiler for ONNX models on heterogeneous systems
… order to build, train, and deploy deep learning models for modern data-driven applications, programs need to be executed on top of specialized heterogeneous systems for better performance. However, programming on those heterogeneous systems remains a fundamental challenge in terms of the …
-
A comparison of neural network and regression models for Navy retention modeling
… thesis evaluates a possible use of artificial neural networks for military manpower and personnel analysis. Two neural network models were constructed to predict the reenlistment behavior of a select group of individuals in the Navy, from a sample of 680 individuals. The data were extracted …
Page 1 of 9