Date of Award
Fall 1992
Document Type
Thesis - Restricted
Degree Name
Master of Science (MS)
Department
Electrical and Computer Engineering
First Advisor
Feng, Xin
Second Advisor
Allgaier, Glen
Third Advisor
Niederjohn, Russell
Abstract
A new combined neural network and data visualization approach is proposed and applied to the capacity planning of computer resources based on a centralized computer system. A back-propagation neural network is employed to model the current system configuration, including memory, central processing unit (CPU) and input/output (I/0) resources. Response predictions are made by estimating future workload demands. The prediction of system response is necessary to determine the lifetime of current computer equipment and also to guarantee performance requirements defined by the organization as service levels. The study demonstrates that the new proposed method provides a better approach for system planning and configuration than traditional methods. Moreover, the process by which the neural network has been uniquely adapted to computer performance prediction makes this new approach convenient for a wide range of general purpose applications of this type. The results are further enhanced by the application of data visualization technology. Visualizing neural network response surfaces provides insights into the operation of the network, the significance of various input classes, and the interpretation of the output response.
Recommended Citation
Moerke, Thomas P., "A Neural Network and Data Visualization Method for Computer Response Prediction and Capacity Planning" (1992). Master's Theses (1922-2009) Access restricted to Marquette Campus. 4644.
https://epublications.marquette.edu/theses/4644