Computer Engineering Commons^™

Investigating Patterns In Convolution Neural Network Parameters Using Probabilistic Support Vector Machines, Yuqiu Zhang

McKelvey School of Engineering Theses & Dissertations

Artificial neural networks(ANNs) are recognized as high-performance models for classification problems. They have proved to be efficient tools for many of today's applications like automatic driving, image and video recognition and restoration, big-data analysis. However, high performance deep neural networks have millions of parameters, and the iterative training procedure thus involves a very high computational cost. This research attempts to study the relationships between parameters in convolutional neural networks(CNNs). I assume there exists a certain relation between adjacent convolutional layers and proposed a machine learning model(MLM) that can be trained to represent this relation. The MLM's generalization ability is evaluated …

Top-Down Construction Cost Estimating Model Using An Artificial Neural Network, Douglas D. Gransberg, H. David Jeong, Ilker Karaca, Brendon Gardner

Ilker Karaca

This report contains the information and background on top-down cost estimating using artificial neural networks (ANN)_to enhance the accuracy of MDT early estimates of construction costs. Upon conducting an extensive review of MDT’s budgeting and cost estimating efforts, and following a survey of agency experts on the identification of the most salient project attributes with the dual-objectives of low effort and high accuracy, a rational method for top-down variable selection is proposed. Selected variables were further tested in their explanatory power of construction costs through the application of two cost estimating methodologies—multiple regression and artificial neural network methodologies. Both methods …

Investigation And Development Of Exhaust Flow Rate Estimation Methodologies For Heavy-Duty Vehicles, Chakradhar Reddy Vardhireddy

Graduate Theses, Dissertations, and Problem Reports

Exhaust gas flow rate from a vehicle tailpipe has a great influence on emission mass rate calculations, as the emission fractions of individual gases in the exhaust are calculated by using the measured exhaust flow rate. The development of high-end sensor technologies and emission pollutant measurement instruments, which can give instantaneous values of volume concentration of pollutants flowing out of the engine are gaining importance because of their ease of operation. The volume concentrations measured can then be used with the instantaneous exhaust flow rate values to obtain mass flow rates of pollutants.

With the recent promulgation of real world …

Optimized Multilayer Perceptron With Dynamic Learning Rate To Classify Breast Microwave Tomography Image, Chulwoo Pack

Electronic Theses and Dissertations

Most recently developed Computer Aided Diagnosis (CAD) systems and their related research is based on medical images that are usually obtained through conventional imaging techniques such as Magnetic Resonance Imaging (MRI), x-ray mammography, and ultrasound. With the development of a new imaging technology called Microwave Tomography Imaging (MTI), it has become inevitable to develop a CAD system that can show promising performance using new format of data. The platform can have a flexibility on its input by adopting Artificial Neural Network (ANN) as a classifier. Among the various phases of CAD system, we have focused on optimizing the classification phase …

Weapon Engagement Zone Maximum Launch Range Approximation Using A Multilayer Perceptron, Brian Michael Birkmire

Browse all Theses and Dissertations

This thesis investigates the use of an artificial neural network (ANN), in particular a Multi-Layer Perceptron (MLP), to perform function approximation on truth data representing a weapon engagement zone's (WEZ) maximum launch range. The WEZ of an air-to-air missile represents the boundaries and zones of effectiveness for a one-vs-one air-to-air combat engagement [13]. The intent is for the network to fuse table lookup and interpolation functionality into a physically compact and computationally efficient package, while improving approximation accuracy over conventional methods. Data was collected from simulated firings of a notional air-to-air missile model and used to train a two layer …

Methanol Recovery During Transesterification Of Palm Oil In A Tio2/Al2o3 Membrane Reactor: Experimental Study And Neural Network Modeling, Abdul Aziz Abdul Raman

Abdul Aziz Abdul Raman

High quality palm oil biodiesel can be produced by combination of alkali transesterification and separation processes in a TiO2/Al 2O3 membrane reactor. Due to the small molecular size, methanol molecules are able to pass through the membrane along with the products. Since methanol is one of the process reactants it is necessary to be recovered. Methanol recovery by means of continuous distillation was employed and the influences of different operational parameters including heating temperature permeate flow rate and reactants ratio were investigated. The results indicate that these parameters have significant effects on the rate of methanol recovery. To simulate the …