Projects / Programmes
Computerised methods in the study of relationships between systems’ parameters
Code |
Science |
Field |
Subfield |
2.07.07 |
Engineering sciences and technologies |
Computer science and informatics |
Intelligent systems - software |
Code |
Science |
Field |
P175 |
Natural sciences and mathematics |
Informatics, systems theory |
P176 |
Natural sciences and mathematics |
Artificial intelligence |
QSAR, bio and photochemical degradation, pollutants, collaborative discrete simulation
Researchers (8)
no. |
Code |
Name and surname |
Research area |
Role |
Period |
No. of publicationsNo. of publications |
1. |
05685 |
Marko Ahčan |
Engineering sciences and technologies |
Researcher |
1997 - 1999 |
19 |
2. |
04855 |
MSc Janez Benkovič |
Engineering sciences and technologies |
Researcher |
1997 - 1999 |
59 |
3. |
12090 |
PhD Danica Dolničar |
Engineering sciences and technologies |
Researcher |
1998 - 1999 |
170 |
4. |
04810 |
PhD Saša Aleksej Glažar |
Social sciences |
Researcher |
1997 - 1999 |
1,228 |
5. |
03183 |
MSc Dragotin Kardoš |
Natural sciences and mathematics |
Researcher |
1997 - 1999 |
135 |
6. |
12091 |
PhD Aleš Musar |
Engineering sciences and technologies |
Researcher |
1997 - 1999 |
107 |
7. |
08957 |
PhD Margareta Vrtačnik |
Natural sciences and mathematics |
Principal Researcher |
1999 |
866 |
8. |
16012 |
PhD Katarina Senta Wissiak Grm |
Social sciences |
Researcher |
1997 - 1999 |
266 |
Organisations (1)
Abstract
The proposed project is a contribution to the methodology of knowledge engineering in identifying a problem, selecting and evaluating parameters and interpretation of the results of methods used in computer supported studies of the relations among the parameters in various processes. The prediction and accuracy of the models for defining the relationships among parameters depend to a great extent on: (1) selection of data teaching and testing sets (examples of compounds and/or processes) for studying relationships, (2) selection and hierarchy of parameters for the description of data set entities, (3) selection of the computer method for identifying relations with regard to the problem definition, (4) iterpretability of results, (5) generalisation of the results to suit relevant types of problems. The assessment methodology is tested on two types of processes: (1) studying interactions of pollutants in the environment and (2) prediction of mass flows in chemical and related processes. For studying the interactions of pollutants with the environment, classification models are employed for the prediction of the relations among electronic and topological parameters and for the properties of substances, algorithms ID3, CART, C4.5 and SIPINA are used. In addition, experimental studies of mechanisms of bio and photocatalytic biodegradation in correlation with the structure of model compounds have been made. For the development of a model for predicting mass flows, a model with collaborative discrete event model-network has been designed, in which the central model (e.g. environmental legislation) has the additional role of synchronising the activities of other models in the network.