Study program:
Mining Engineering (II semester -PhD) |
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Name of subject: The Application of Soft Computing Methods in Mining Engineering |
Instructors:
Prof. Igor Miljanović |
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Status: Optional |
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ECTS: 10 |
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Prerequisites: - |
Course Objectives:
Acquainting with soft computing methods and their application in mining engineering. |
Learning Outcomes:
Student is trained to identify problems that can be solved by soft computing methods and the development of soft computing models of occurrences and processes in mining engineering: genetic algorithms, fuzzy logic, neural networks and hybrid methods. |
Content:
Theory teaching
Introduction. Concept and historical perspective. Review of soft computing methods. Classification. Areas of application. Introduction to fuzzy logic. General concept. Fuzzy sets. Fuzzy arithmetic. Fuzzy inference models: Mamdani, Takagi-Sugeno. Fuzzy models of occurrences and processes in mining engineering. Introduction to genetic algorithms. Development. Genetic algorithms elements. Application. Seminal paper preparatory session Introduction to neural networks. Neural networks model. Development. Neural networks training. Neural networks implementation. Soft computing hybrid methods. Other soft computing methods. Practical teaching
Fuzzy linear optimization in surface mining. Fuzzy modelling in mineral processing. Fuzzy model for predicting the blast induced ground vibrations in open pit mines. Soft computing methods in petroleum engineering. Mining method selection by soft computing methods. Adaptive genetic algorithms in mining engineering design. Neural-fuzzy system in mineral processing modelling. Seminal paper discussion and analysis. |
Suggested Reading List:
- Karr C.L., Practical Applications of Computational Intelligence for Adaptive Control, CRC Press, 1999.
- Mitchell M., An introduction to Genetic Algorithms, MIT Press, 1999.
- Rutkowski L., Neuro-fuzzy systems, Structures, Learning and Performance Evaluation, Kluwer, 2004.
- Zilouchian A., Jamshidi M., (eds), Intelligent Control Systems Using Soft Computing Methodologies, CRC Press, 2001.
- Reznick L., Fuzzy controllers, Newnes, 1997.
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Conduct of the Course:
Oral presentation, practical work (calculation exercises), computer work. |
Fund hours:
| Lectures |
Exercises |
Other forms of teaching |
Study research |
| 4 |
0 |
0 |
0 |
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Assessment:
| Final Exam |
ECTS |
| Oral Exam | 30 |
| Classwork Assessment |
ECTS |
| Written tests | 20 | | Seminars | 50 |
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Additional Assessment Criteria: - |
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