| Author: |
Joanna Chimiak−Opoka |
| Supervisor: |
prof. Andrzej Piegat |
| University: |
Technical University of Szczecin Faculty of Computer Science |
| Readers: |
prof. Danuta Rutkowska Częstochowa University of Technology Department of Computer Engineering prof. Jacek Łęski Silesian University of Technology Faculty of Automatic Control, Electronics and Computer Science Division of Biomedical Electronics |
| Defence: | 2002-12-10 |
| Key-words: |
dimensionality reduction,
preliminary input selection,
approximation of functions |
| Description: |
The goal of the thesis was designing preliminary input selection
method for multidimensional models which would respect real data
points distribution and use artificial intelligence.
The problem of input selection for multidimensional models has
practical importance for construction mathematical models
of real systems.
The methods for input selection are used in many branches,
e.g. pattern recognition, modelling, control and decision making.
The thesis is devoted to approximation of functions.
A new criterion of estimating input significance was proposed.
According to the criterion, significance of the input depends
on directional curvature of the model.
An algorithm for evaluating significance of inputs
is based on cellular subdivision of input space respecting
to the data points distribution.
Proposed approach was theoretically analysed and the algorithm
was tested on sets of artificial and real data points.
|
| Application: |
The algorithm for preliminary input selection for multidimensional
modelling was presented. The algorithm may be applied in many problems
related to approximation of functions. It can be used in technical or
economical problems. Depending on number of data points from system it
uses a different accuracy (limited number of cells, subspaces
analysis). The algorithm enables also inputs interconnection analysis.
|