COURSE UNIT TITLE

: ARTIFICIAL INTELLIGENCE APPLICATIONS FOR GEOSCIENCES

DEGREE PROGRAMMES

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
MTS 3036 ARTIFICIAL INTELLIGENCE APPLICATIONS FOR GEOSCIENCES ELECTIVE 2 0 0 3

Offered By

Faculty of Engineering

Level of Course Unit

First Cycle Programmes (Bachelor's Degree)

Course Coordinator

ASSOCIATE PROFESSOR ILKNUR KAFTAN

Offered to

Textile Engineering
Mechanical Engineering
Mechanical Engineering (Evening)
Faculty of Engineering
Geophysical Engineering
Mining Engineering
Environmental Engineering
Civil Engineering
Civil Engineering (Evening)
Geological Engineering

Course Objective

The applications of artificial intelligence methods in geosciences were aimed to be understood by students.

Learning Outcomes of the Course Unit

1   1.To be able to define / understand / learn artificial intelligence methods
2   2.To have knowledge about the application areas of artificial intelligence methods
3   3.To be able to understand the advantages of artificial intelligence applications
4   4. To understand the applications of artificial intelligence methods in geosciences
5   5.To establish a relationship between earth sciences problems and artificial intelligence applications
6   6.To be able to produce solutions for geosciences problems by using artificial intelligence methods

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 1. Theory of intelligence
2 2. Intoduction to artificial intelligence and history of artificial intelligence
3 3. Application fields of artificial intelligence
4 4.Artificial intelligence and learning
5 5.Artificial intelligence and learning
6 6.Artificial intelligence methods and their properties
7 7.Artificial intelligence methods and their properties
8 8.Artificial intelligence methods and their properties
9 9. Advantages and disadvantages of artificial intelligence
10 10.Programming languages used in artificial intelligence applications
11 11.Artificial intelligence applications for geosciences ( modeling of subsurface structures 1)
12 12.Artificial intelligence applications for geosciences ( modeling of subsurface structures 2)
13 13.Artificial intelligence applications for geosciences (Seismology)
14 14.Artificial intelligence applications for geosciences (Geothermal)

Recomended or Required Reading

Textbook(s):
Introduction to Artificial Intelligence, Wolfgang Ertel, Springer, 2011.
Artificial Intelligence and Dynamic systems for Geophysical Applications, Alexei Gvishiani and Jacques O. Dubois, Springer, 2002

Supplementary Book(s):
Yapay Zeka Uygulamaları, Prof.Dr. Çetin Elmas, Seçkin Akademik ve Mesleki Yayınlar, Dördüncü Baskı, 2018 (in Turkish).
Yapay Sinir Ağları, Prof.Dr Ercan Öztemel, Papatya Yayıncılık, 2012 (in Turkish).
Bulanık Mantık Uzman Sistemler ve Denetleyiciler, Nazife Baykal ve Timur Beyan, Bıçaklar Kitabevi, 2004 (in Turkish).

Planned Learning Activities and Teaching Methods

Students will follow the course from presentations, lecture notes and relevant books.

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA
1 MTE MIDTERM EXAM
2 PRJ PROJECT
3 FIN FINAL EXAM
4 FCG FINAL COURSE GRADE MTE * 0.30 + PRJ * 0.20 + FIN * 0.50
5 RST RESIT
6 FCGR FINAL COURSE GRADE (RESIT) MTE * 0.30 + PRJ * 0.20 + RST * 0.50


*** Resit Exam is Not Administered in Institutions Where Resit is not Applicable.

Further Notes About Assessment Methods

None

Assessment Criteria

Homework Assignments: 20% (LO1,2,3,4,5)
Mid-term exams: 30% (LO1,2,3)
Final Exam: 50% (LO1,2,3,4,5,6)

Language of Instruction

Turkish

Course Policies and Rules

To be announced.

Contact Details for the Lecturer(s)

Dokuz Eylül Üniversitesi Mühendislik Fakültesi Jeofizik Mühendisliği Bölümü Tınaztepe Kampüsü

ilknur.kaftan@deu.edu.tr

Office Hours

Friday 15:00-17:00

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 14 2 28
Preparations before/after weekly lectures 13 3 39
Final 1 2 2
Midterm 1 2 2
TOTAL WORKLOAD (hours) 71

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10PO.11
LO.135
LO.253
LO.334
LO.444
LO.54
LO.64

CONTACT INFORMATION
Dokuz Eylül Üniversitesi Cumhuriyet Bulvarı No: 144 35210 Alsancak / İZMİR
Phone: +90(232) 412 12 12 - Fax: +90 (232) 464 81 35

Copyright 2015 DEÜ. BİD

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