dc.contributor.author | Kakooza, Abraham Jerry | |
dc.date.accessioned | 2021-02-11T08:58:11Z | |
dc.date.available | 2021-02-11T08:58:11Z | |
dc.date.issued | 2021-02-03 | |
dc.identifier.citation | Kakooza, A. J. (2021). Design of a machine learning based system for pharmaceutical purchases. Unpublished undergraduate dissertation. Makerere University. Kampala, Uganda. | en_US |
dc.identifier.uri | http://hdl.handle.net/20.500.12281/8769 | |
dc.description | A report submitted in partial fulfillment of the requirements for the Degree of Bachelor of Science in Telecommunications Engineering
at Makerere University | en_US |
dc.description.abstract | To obtain inherent laws from vast amounts of pharmaceutical sales data and to provide
valuable information to pharmacy managers, this work validates di erent methods and
approaches to perform a sales forecast. Part of the data is used to train a neural network
algorithm, with backpropagation for some methods, step by step, where shallow nets face
selected scenarios, with di erent space-time data considerations.
In each method, by using a sum of square di erences, and a peak search procedure, a reasonable
quality in the obtained abstract representations is pursued. First, an auto-encoder
is trained to develop in its hidden layer neural data abstractions about a random-moving
window. Thereafter by using the abstraction of the net plus recently captured information, a
second shallow net is trained to produce its own one-day ahead estimates, using new timing
and data procedures. After training, the whole stacked system's performance is compared
with the naive forecast scenario's mean square error and if it's a better value, the method
is used to produce stable daily forecasting for assorted products and periods. The system
has been tested in real-time with real data. | en_US |
dc.language.iso | en | en_US |
dc.subject | Machine learning based system | en_US |
dc.subject | Pharmaceutical purchases. | en_US |
dc.title | Design of a machine learning based system for pharmaceutical purchases. | en_US |
dc.type | Thesis | en_US |