Učni načrt predmeta

Predmet:
Avtomatizirano modeliranje dinamičnih sistemov s primeri uporabe v ekologiji
Course:
Automated Modeling of Dynamic Systems with Ecological Applications
Študijski program in stopnja /
Study programme and level		 Študijska smer /
Study field		 Letnik /
Academic year		 Semester /
Semester
Ekotehnologije, 3. stopnja / 1 1
Ecotechnologies, 3rd cycle / 1 1
Vrsta predmeta / Course type
Izbirni / Elective
Univerzitetna koda predmeta / University course code:
EKO3-787
Predavanja
Lectures		 Seminar
Seminar		 Vaje
Tutorial		 Klinične vaje
work		 Druge oblike
študija		 Samost. delo
Individ. work		 ECTS
15 15 15 105 5

*Navedena porazdelitev ur velja, če je vpisanih vsaj 15 študentov. Drugače se obseg izvedbe kontaktnih ur sorazmerno zmanjša in prenese v samostojno delo. / This distribution of hours is valid if at least 15 students are enrolled. Otherwise the contact hours are linearly reduced and transfered to individual work.

Nosilec predmeta / Course leader:
prof. dr. Sašo Džeroski
Sodelavci / Lecturers:
Jeziki / Languages:
Predavanja / Lectures:
slovenščina, angleščina / Slovenian, English
Vaje / Tutorial:
Pogoji za vključitev v delo oz. za opravljanje študijskih obveznosti:
Prerequisites:

Izpolnjeni morajo biti pogoji za vpis na doktorski študij: zaključena druga stopnja bolonjskega študija ali diploma univerzitetnega študijskega programa. Potrebna so tudi osnovna znanja biologije oz. ekologije ter računalništva oz. informatike.

Students must fulfill the formal requirements for enrolling to the doctoral study program: completed Bologna second-cycle study program or an equivalent pre-Bologna university study program. Basic knowledge of biology or ecology and computer science or informatics is also required.

Vsebina:
Content (Syllabus outline):

Uvod: Modeliranje dinamičnih sistemov:
Modeliranje prostora stanj in vhodov-izhodov Modeli v diskretnem in zveznem času
Parametrični in neparametrični modeli
Kvalitativni in kvantitativni modeli

Sklepanje s parametričnimi modeli:
Simulacija
Identifikacija oz. optimizacija parametrov Strukturna identifikacija

Učenje neparametričnih modelov v diskretnem času

Učenje procesno osnovanih modelov:
Predstavitev procesnih modelov
Metode za učenje procesnih modelov

Primeri uporabe oz. študije primerov avtomatiziranega modeliranja ekosistemov in epidemij.

Introduction: Modeling dynamic systems:
State-space and input-output models
Discrete and continuous-time models
Parametric and non-parametric models
Qualitative and quantitative models

Reasoning with parametric models:
Simulation
Parameter fitting / identification
Structure identification

Learning non-parametric discrete time models

Learning process-based models:
Representation: Entities, Processes, Libraries
Learning methods: LAGRAMGE, ProBMoT

Applications:
Case studies in automated modeling of aquatic ecosystems and epidemiology

Temeljna literatura in viri / Readings:

Izbrana poglavja iz naslednjih knjig: / Selected chapters from the following books:
- Mobus, G.E., and Kalton, M.C. Principles of Systems Science. Springer, 2015. ISBN 978-1-493-91919-2.
- Joergensen, S.E., and Fath, B. Fundamentals of Ecological Modelling: Applications in Environmental
Management and Research. Elsevier, 2011. ISBN 978-0-444-53567-2.
- Džeroski S., and Todorovski L., editors. Computational Discovery of Scientific Knowledge:
Introduction, Techniques, and Applications in Environmental and Life Sciences. Springer, 2007. ISBN 978-3-540-73919-7.
- Hannon, B., and Ruth, M. Modeling Dynamic Biological Systems. 2nd edition. Springer, 2014. ISBN
978-3-319-05614-2.

Cilji in kompetence:
Objectives and competences:

Cilj predmeta je seznaniti študenta s področjem avtomatiziranega modeliranja dinamičnih sistemov, vključno z osnovnimi pojmi in sodobnimi metodami.

Kompetence študenta z uspešno zaključenim predmetom bodo vključevale razumevanje osnovnih pojmov, poznavanje sodobnih metod in sposobnost samostojne uporabe teh metod pri novih nalogah modeliranja ekosistemov in okoljskih sistemov.

The course objective is to familiarize the student with the field of automated modeling of dynamic systems, including basic concepts and state of the art methods.

The competencies of the students successfully completing this course will include the understanding of basic concepts from the field, familiarity with the state-of-the art methods, and capability of independent use of the methods in new practical projects of modeling ecological and environmental systems.

Predvideni študijski rezultati:
Intendeded learning outcomes:

- Dobiti pregled obstoječih nalog in metod avtomatiziranega modeliranja dinamičnih sistemov ter primerov njihove uporabe v ekologiji
- Pridobiti sposobnost uporabe obstoječih metod na novih problemih
- Pridobiti sposobnost ugotavljanja primernosti različnih pristopov za avtomatizirano modeliranje različnih ekosistemov

- Acquiring an overview of existing tasks and methods in automated modelling of dynamic systems and case studies of their use in ecology
- Obtaining the ability to apply existing methods to new problems
- Obtaining the ability to identify the best methodological approach available for solving specific problems of automated modeling of different ecosystems

Metode poučevanja in učenja:
Learning and teaching methods:

Predavanja, konzultacije, samostojno delo

Lectures, consultations, individual work

Načini ocenjevanja:
Delež v % / Weight in %
Assesment:
Ustni izpit
50 %
Oral exam
Seminarska naloga
25 %
Seminar work
Ustni zagovor
25 %
Oral defense
Reference nosilca / Lecturer's references:
1. Aleksovski, D., Kocijan, J., and Džeroski, S. (2015). Model-tree ensembles for noise-tolerant system identification. Advanced Engineering Informatics, 29(1): 1-15. DOI: 10.1016/j.aei.2014.07.008
2. Simidjievski, N., Todorovski, L., and Džeroski, S. (2015). Learning ensembles of population dynamics models and their application to modelling aquatic ecosystems. Ecological Modelling, 306: 305-317. DOI: 10.1016/j.ecolmodel.2014.08.019
3. Simidjievski, N., Todorovski, L., and Džeroski, S. (2015). Predicting long-term population dynamics with bagging and boosting of process-based models. Expert Systems with Applications, 42(22): 8484-8496. DOI: 10.1016/j.eswa.2015.07.004
4. Škerjanec, M., Atanasova, N., Čerepnalkoski, D., Džeroski, S., and Kompare, B. (2014). Development of a knowledge library for automated watershed modeling. Environmental Modelling and Software, 54: 60-72.DOI: 10.1016/j.envsoft.2013.12.017
5. Taškova, K., Šilc, J., Atanasova, N., and Džeroski, S. (2012). Parameter estimation in a nonlinear dynamic model of an aquatic ecosystem with meta-heuristic optimization. Ecological Modelling, 226(1): 36-61. DOI: 10.1016/j.ecolmodel.2011.11.029