Diego Santamaría; Álvaro de Ramón MSE-2008-20, pp. 82. TEK/avd. för programvaruteknik, 2008.
Facilitating the decision making process using
models and patterns is viewed in this thesis to be really
helpful. Data mining is one option to accomplish this
task. Data mining algorithms can show all the relations
within given data, find rules and create behavior
patterns. In this thesis seven different types of data
mining algorithms are employed.
Monte Carlo is a statistical method that is used in
the developed prototype to obtain random data and to
simulate different scenarios. Monte Carlo methods are
useful for modeling phenomena with significant
uncertainty in the inputs.
This thesis presents the steps followed during the
development of a web-tool prototype that uses data
mining techniques to assist decision-makers of port
planning to make better forecasts using generated data
from the Monte Carlo simulation.
The prototype generates random port planning
forecasts using Monte Carlo simulation. These forecasts
are then evaluated with several data mining algorithms.
Then decision-makers can evaluate the outcomes of the
prototype (rules, decision tress and regressions) to be
able to make better decisions.