COURSE DESCRIPTION

Advanced Data Processing Methods in Geosciences


Programme:

Environmental and Regional Studies (3rd level)

Modul:
4D Earth

Course code: DIZ01
Study year: None


Course principal:
Asst. Prof. Gorazd Žibret, PhD

ECTS: 6

Workload: lectures 10 hours, seminar 10 hours, tutorial 10 hours, individual work 150 hours

Course type: general elective

Languages: Slovene, English

Learning and teaching methods: lectures, discussion classes, seminars, independent work assignments, consultations, e-learning.

 

Course syllabus

Prerequisits:

Second-cycle Bologna degree in the relevant track or a university (level VII) degree

 

Content (Syllabus outline):

  1. Introduction to artificial intelligence
  2. Data in geosciences and its specifics:
    • compositional and
    • orientational data,
    • outliers,
    • attributive data
  3. Neural networks:
    • properties,
    • types,
    • topologies,
    • feed-forward and
    • recurrent networks
  4. Neural network machine learning paradigms:
    • supervised,
    • unsupervised,
    • reinforced,
    • evolutionary
  5. Data preparation and validation methods
  6. Positive and negative aspects of neural networks
  7. Approach to the problem
  8. Examples from practice
  9. Other methods of artificial intelligence:
    • linear and multiple regression,
    • decision trees,
    • support vector machines,
    • fuzzy logic
  10. individual work

 

Readings:

  • Nielsen A.M. Neural Networks and deep learning. Determination press, 2015, 224 p.
  • https://static.latexstudio.net/article/2018/0912/neuralnetworksanddeeplearning.pdf
  • http://neuralnetworksanddeeplearning.com/
  • Haykin S. Neural Networks and learning machines, 3rd ed. Prentice Hall, 2009. https://dai.fmph.uniba.sk/courses/NN/haykin.neural-networks.3ed.2009.pdf
  • ŽIBRET, Gorazd, ŠAJN, Robert. Hunting for geochemical associations of elements: factor analysis and self-organising maps. Mathematical geology. 2010, vol. 42, no. 6, str. 681-703. DOI: 10.1007/s11004-010-9288-3.
  • ŽIBRET, Gorazd, ŠAJN, Robert, ALIJAGIĆ, Jasminka, STAFILOV, Trajče. Use of neural networks in the geochemical data interpretation. Zeitschrift für geologische Wissenschaften. 2012, bd. 40, h. 4/5, str. 253-266.
  • CERAR, Sonja, MEZGA, Kim, ŽIBRET, Gorazd, URBANC, Janko, KOMAC, Marko. Comparison of prediction methods for oxygen-18 isotope composition in shallow groundwater. Science of the total environment. 2018, vol. 631-632, str. 358-368. DOI: 10.1016/j.scitotenv.2018.03.033.

 

Objectives and competences:

Student knows principles of artificial intelligence, and can use neural networks for solving problems

 

Intended learning outcomes:

The student is able to independently apply neural network methods using the MemBrain simulator. He/she knows how to analyse a problem, determine suitable network topologies, prepare data, train the network, properly evaluate the resulting model and use it in practice.

 

Learning and teaching methods:

  • Lectures
  • Seminar
  • Independent work assignments
  • Consultations
  • e-Learning

 

MODULE GENERAL ELECTIVE COURSES

Advanced Data Processing Methods in Geosciences

Asst. Prof. Gorazd Žibret, PhD,

ECTS: 6

Advanced Studies of the Earth’s Subsurface

Asst. Prof. Marjana Zajc, PhD,

ECTS: 6

Geo-Resource Management Principles

Asst. Prof. Gorazd Žibret, PhD,

ECTS: 6

Geochemistry of the Anthropocene

Asst. Prof. Miloš Miler, Ph. D. ,

ECTS: 6

Geomorphology in Geohazard Studies

Asst. Prof. Petra Jamšek Rupnik, PhD,

ECTS: 6

Interdisciplinary Research in Earthquake Geology

Asst. Prof. Petra Jamšek Rupnik, PhD,

ECTS: 6

Landslide Management

Asst. Prof. Mateja Jemec Auflič, PhD,

ECTS: 6