222-0503/02 – Urban development modeling (MOD)

Gurantor department	Department of Urban Engineering	Credits	3
Subject guarantor	Ing. Martin Ferko, Ph.D.	Subject version guarantor	Ing. Martin Ferko, Ph.D.
Study level	undergraduate or graduate	Requirement	Compulsory
Year	1	Semester	winter
		Study language	English
Year of introduction	2019/2020	Year of cancellation
Intended for the faculties	HGF, FAST	Intended for study types	Follow-up Master, Master

Instruction secured by
Login	Name	Tuitor	Teacher giving lectures
FER031	Ing. Martin Ferko, Ph.D.
MUR069	Ing. Tereza Majstríková, Ph.D.

Extent of instruction for forms of study
Form of study	Way of compl.	Extent
Full-time	Credit	0+3
Part-time	Credit	0+14

Subject aims expressed by acquired skills and competences

The course is aimed at students with an introduction of implementation issues simple mathematical models. The students in the course will enhance their ability to use computer technology to technical and economic calculations. The main element is the establishment of a dynamic model of the aging building and its more detailed analysis. The model is affected by the interaction between aging and structural elements of building an object in time according to the discharge procedure.

Teaching methods

Tutorials

Summary

Compulsory literature:

BOLONO, F.,ODORIZZI, S.: Numerical simulation of Foundry Processes, Program Leonardo da Vinci, 2001 HLAVSA, T.: Statistics I. V Praze: Česká zemědělská univerzita v Praze, Provozně ekonomická fakulta, 2016. ISBN 978-80-213-2659-0. EVERITT, B. et al.: Cluster analysis. 5th ed. Chichester: John Wiley & Sons, 2011. xii, 330 s. Wiley series in probability and statistics. ISBN 978-0-470-74991-3. WANG, XIAOYAN; BAI, YANPING: SpringerPlus. 9/27/2016, Vol. 5 Issue 1, p1-15. 15p. DOI: 10.1186/s40064-016-3329-4. LEBLANC, L., GALBRETH, M.: In: Interfaces. 37(4):370-382; The Institute for Operations Research and the Management Sciences (INFORMS), 2007

Recommended literature:

BUCHANAN, J.L.: Numerical Methods and Analysis, McGraw-Hill, 1992 NABARESEH, Stephen. Predictive analytics: a data mining technique in customer churn management for decision making: Prediktivní analytika: technika data miningu pro rozhodování s využitím v řízení odchodu zákazníků : doctoral thesis summary. Zlín: Tomas Bata University in Zlín, 2017. ISBN 978-80-7454-649-5.

Way of continuous check of knowledge in the course of semester

Written final test, control of read professional literature, conversational topics.

E-learning

Other requirements

At least 70% attendance at the exercises. Absence, up to a maximum of 30%, must be excused and the apology must be accepted by the teacher (the teacher decides to recognize the reason for the excuse). Tasks assigned on the exercises must be hand in within the dates set by the teacher.

Prerequisities

Subject has no prerequisities.

Co-requisities

Subject has no co-requisities.

Subject syllabus:

Topics: 1. Process Modelling - Introduction parameterization 2. Follow-up processes 3. Introduction + creation of a dynamic model 4. Build a model calculation of the aging 5. Model of Asset Management (Buildpass) 6. Risk, risk analysis, optimization 7. The model of competitive relations Contents exercises 1) The model dependence of elements in time (\"splines\") 2) Parameterization of the model dependence of elements in time 3) Dynamic model of aging object (the object) 4) Development of calculation model of aging a) tuning b) extensions (external influences, risks, etc.) 5) Application of risk in a model of aging

Conditions for subject completion

Full-time form (validity from: 2019/2020 Winter semester)

Task name	Type of task	Max. number of points (act. for subtasks)	Min. number of points	Max. počet pokusů
Credit	Credit	100	51	3

Mandatory attendence participation: At least 70% attendance at the exercises. Absence, up to a maximum of 30%, must be excused and the apology must be accepted by the teacher (the teacher decides to recognize the reason for the excuse). Tasks assigned on the exercises must be hand in within the dates set by the teacher. Final written test.

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Conditions for subject completion and attendance at the exercises within ISP:

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Occurrence in study plans

Academic year	Programme	Form	Study language	Tut. centre	Year	Type of duty
2023/2024	(N0732A260016) Civil Engineering - Municipal Engineering	K	English	Ostrava	1	Compulsory	study plan
2023/2024	(N0732A260016) Civil Engineering - Municipal Engineering	P	English	Ostrava	1	Compulsory	study plan
2022/2023	(N0732A260016) Civil Engineering - Municipal Engineering	K	English	Ostrava	1	Compulsory	study plan
2022/2023	(N0732A260016) Civil Engineering - Municipal Engineering	P	English	Ostrava	1	Compulsory	study plan
2021/2022	(N0732A260016) Civil Engineering - Municipal Engineering	P	English	Ostrava	1	Compulsory	study plan
2021/2022	(N0732A260016) Civil Engineering - Municipal Engineering	K	English	Ostrava	1	Compulsory	study plan
2020/2021	(N0732A260016) Civil Engineering - Municipal Engineering	P	English	Ostrava	1	Compulsory	study plan
2020/2021	(N0732A260016) Civil Engineering - Municipal Engineering	K	English	Ostrava	1	Compulsory	study plan
2019/2020	(N0732A260016) Civil Engineering - Municipal Engineering	P	English	Ostrava	1	Compulsory	study plan
2019/2020	(N0732A260016) Civil Engineering - Municipal Engineering	K	English	Ostrava	1	Compulsory	study plan

Occurrence in special blocks

Block name	Academic year	Form of study	Study language	Year	W	S	Type of block	Block owner
BIP - How can urban commons transform an industrial and mining region? Case study: Ostrava 1	2022/2023	Full-time	English				Choice-compulsory	223 - Department of Building Materials and Diagnostics of Structures	stu. block
ECTS Bc.-Mgr.	2022/2023	Full-time	English				Choice-compulsory	200 - Faculty of Civil Engineering - Dean's Office	stu. block

Assessment of instruction

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