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 13 of 13 for “"Neural Network Modeling"”.
-
Knowledge-based artificial neural network modeling assessment: integrating heterogeneous genomics data to uncover lifespan regulation
… continues to grow. More specifically, genetic modeling and neural network building are gaining interest as it becomes a fundamental piece of most model building we see today. We propose a Knowledge-Based Artificial Neural Network (KBANN) to predict phenotype while providing insight to effected …
-
Neural network modeling of the dynamics of autonomous underwater vehicles for Kalman filtering and improved localization
… time. This research explores the use of a Neural Network architecture to replace these dynamic equations. Initial experiments have showed promising results for the Neural Network although modifications will be required before the controller can be made universally applicable.
-
Neural Network Prediction of Math and Reading Proficiency as Reported in the Educational Longitudinal Study 2002 Based on Non-Curricular Variables
… performance of a three-layer back propagation neural network to that of traditional multiple linear regression in predicting math and reading proficiency from 103 non-curricular variables collected in the National Center for Educational Statistics' 2002 Educational Longitudinal Study. The …
-
Intelligent Instability Detection for Islanding Prediction
… prediction procedures using decision tree and neural network modeling. The islanding in the power system define as a separation of the coherent group of generators from the rest of the system due to contingencies, in the case that all generators are coherent together after introducing a fault, …
-
Spiking neural networks and their applications
<p>"Artificial neural networks (ANNs) have been developed as adaptable, robust function approximators for at least the last quarter-century. They have progressed through two generations, and the third is now under development. Spiking neural networks (SNNs) seek to improve on previous generations …
-
Analysis of the cross-section of equity returns on the JSE Securities Exchange based on linear and nonlinear modeling techniques
… returns. A blended approach combining a linear modeling technique with a nonlinear artificial neural network technique is developed to identify future potential top performing shares on the JSE. 1. Both linear and nonlinear models identify book-value-to-price and cash flow-to-price as …
-
Memory-related cognitive modulation of human auditory cortex: Magnetoencephalography-based validation of a computational model
… a novel approach for integrating 'bottom-up' (neural network modeling) and 'top-down' (experiment) methods to study the dynamics of cortical circuits correlated to shortterm memory (STM) processing that underlie the task-specific modulation of human auditory perception during performance of the …
-
Process modeling and optimization using industrial semiconductor fabrication data
… databases. This research explores the use of a neural network modeling and genetic algorithm optimization method with these different datasets. The focus is on a high-aspect-ratio etch process across the different fabs and production stages. Models are built from process input variables to …
-
A Comparison Study of Carbon Dioxide Absorption Performance in MEA and Blended Amine Solvents for Post-combustion Process: Experiment, Modeling and Simulation
… with the prediction results from the Artificial Neural Network model and the simulation results using MATLAB and ProMax, respectively. The prediction results from ANN model confirmed that the CO2 equilibrium solubility of 2M MDEA+3M PZ was higher than other blend amine solvents and the …
-
Symbolic and connectionist machine learning techniques for short-term electric load forecasting
This work applies connectionist neural network learning techniques and symbolic machine learning techniques to the problem of short-term electric load forecasting. The short-term electric load forecasting problem considered here is the prediction of bus loads one day ahead. The forecast quantities …
-
Feed-Forward Neural Network (FFNN) Based Optimization Of Air Handling Units: A State-Of-The-Art Data-Driven Demand-Controlled Ventilation Strategy
… estimation accuracy. In this study, feed-forward neural network algorithm (FFNN) was proposed to estimate the zone occupancy using CO2 concentrations, observed occupancy data and the zone schedule. The occupancy prediction result was then utilized to optimize supply fan operation of the air …
-
Advanced modeling techniques for electroactive polymers transducers
… IP2C, basato sulla modellizzazione con reti neurali. in particolare il modello proposto tiene conto della dipendenza dall'umidità del dispositivo.
-
Prediction of Whole-body Lifting Kinematics using Artificial Neural Networks
… in this task development process. Artificial neural networks were used in this investigation to achieve these predictions. As input, these networks received information about lift characteristics (e.g. target location, movement duration) and returned a predicted set of joint angles. Two types …