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Showing 25 course outlines from 6720 matches

2326

ENGSCI 712

: Computational Algorithms for Signal Processing
2024 Semester Two (1245)
Advanced topics in mathematical modelling and computational techniques, including topics on singular value decomposition, Principle Component Analysis and Independent Component Analysis, eigen-problems, and signal processing (topics on neural network models such as the multi-layer perception and self organising map).
Subject: Engineering Science
Prerequisite: 15 points from ENGSCI 311, 313, 314
2327

ENGSCI 712

: Computational Algorithms for Signal Processing
2023 Semester Two (1235)
Advanced topics in mathematical modelling and computational techniques, including topics on singular value decomposition, Principle Component Analysis and Independent Component Analysis, eigen-problems, and signal processing (topics on neural network models such as the multi-layer perception and self organising map).
Subject: Engineering Science
Prerequisite: 15 points from ENGSCI 311, 313, 314
2328

ENGSCI 712

: Computational Algorithms for Signal Processing
2022 Semester Two (1225)
Advanced topics in mathematical modelling and computational techniques, including topics on singular value decomposition, Principle Component Analysis and Independent Component Analysis, eigen-problems, and signal processing (topics on neural network models such as the multi-layer perception and self organising map).
Subject: Engineering Science
Prerequisite: 15 points from ENGSCI 311, 313, 314
2329

ENGSCI 712

: Computational Algorithms for Signal Processing
2021 Semester Two (1215)
Advanced topics in mathematical modelling and computational techniques, including topics on singular value decomposition, Principle Component Analysis and Independent Component Analysis, eigen-problems, and signal processing (topics on neural network models such as the multi-layer perception and self organising map).
Subject: Engineering Science
Prerequisite: 15 points from ENGSCI 311, 313, 314
2330

ENGSCI 712

: Computational Algorithms for Signal Processing
2020 Semester Two (1205)
Advanced topics in mathematical modelling and computational techniques, including topics on singular value decomposition, Principle Component Analysis and Independent Component Analysis, eigen-problems, and signal processing (topics on neural network models such as the multi-layer perception and self organising map).
Subject: Engineering Science
Prerequisite: 15 points from ENGSCI 311, 313, 314
2331

ENGSCI 713

: Mathematical Modelling for Professional Engineers
2023 Semester One (1233)
Mathematical modelling techniques required by professional engineers, such as partial and ordinary differential equations, differentiation and integration, vector calculus, linear algebra, analytical and numerical methods, industrial statistics, and data analysis.
Subject: Engineering Science
Prerequisite: ENGSCI 211 or 213
Restriction: ENGSCI 311, 313, 314
2332

ENGSCI 721

: Data-centric Engineering for Physical Systems
2025 Semester Two (1255)
Mathematical modelling of complex physical systems, including model development, parameterisation and evaluation, illustrated using examples from current research and industry. Inverse problems and uncertainty quantification for physical models in engineering and science, including principles of uncertainty propagation for linear and nonlinear physical models given real-world data, and connections to physics-informed machine learning.
Subject: Engineering Science
Prerequisite: 15 points from COMPSCI 101, ENGGEN 131, MATHS 162, 199; and either 15 points from ENGSCI 311, 313, 314, or MATHS 260 and either STATS 210 or 225
2333

ENGSCI 721

: Data-centric Engineering for Physical Systems
2023 Semester Two (1235)
Mathematical modelling of complex physical systems, including model development, parameterisation and evaluation, illustrated using examples from current research and industry. Inverse problems and uncertainty quantification for physical models in engineering and science, including principles of uncertainty propagation for linear and nonlinear physical models given real-world data, and connections to physics-informed machine learning.
Subject: Engineering Science
Prerequisite: Departmental approval
2334

ENGSCI 721

: Advanced Numerical Methods
2021 Semester Two (1215)
An advanced course on finite elements, boundary elements and finite differences.
Subject: Engineering Science
Prerequisite: Departmental approval
2335

ENGSCI 740

: Computational Engineering for Physical Systems
2025 Semester One (1253)
Principles and practice for modelling complex physical systems. Applications in biomechanics, fluid mechanics and solid mechanics. Including topics such as large deformation elasticity theory applied to soft tissues, inviscid flow theory, compressible flows, viscous flows, meteorology, oceanography, coastal ocean modelling, mixing in rivers, fracture, composite materials and geomechanics. Underlying theories, computational techniques and industry applications explored using commercial software.
Subject: Engineering Science
Prerequisite: BIOMENG 321 or ENGSCI 343
2336

ENGSCI 740

: Computational Engineering for Physical Systems
2024 Semester One (1243)
Principles and practice for modelling complex physical systems. Applications in biomechanics, fluid mechanics and solid mechanics. Including topics such as large deformation elasticity theory applied to soft tissues, inviscid flow theory, compressible flows, viscous flows, meteorology, oceanography, coastal ocean modelling, mixing in rivers, fracture, composite materials and geomechanics. Underlying theories, computational techniques and industry applications explored using commercial software.
Subject: Engineering Science
Prerequisite: BIOMENG 321 or ENGSCI 343
2337

ENGSCI 740

: Computational Engineering for Physical Systems
2023 Semester One (1233)
Principles and practice for modelling complex physical systems. Applications in biomechanics, fluid mechanics and solid mechanics. Including topics such as large deformation elasticity theory applied to soft tissues, inviscid flow theory, compressible flows, viscous flows, meteorology, oceanography, coastal ocean modelling, mixing in rivers, fracture, composite materials and geomechanics. Underlying theories, computational techniques and industry applications explored using commercial software.
Subject: Engineering Science
Prerequisite: BIOMENG 321 or ENGSCI 343
2338

ENGSCI 740

: Advanced Mechanics in Research and Technology
2020 Semester One (1203)
Applications of continuum mechanics to problems in biomechanics, fluid mechanics and solid mechanics. Including topics such as large deformation elasticity theory applied to soft tissues, inviscid flow theory, compressible flows, viscous flows, meteorology, oceanography, coastal ocean modelling, mixing in rivers and estuaries. Fracture, composite materials and geomechanics.
Subject: Engineering Science
Prerequisite: BIOMENG 321 or ENGSCI 343
2339

ENGSCI 746

: Advanced Modelling and Simulation in Computational Mechanics
2025 Semester Two (1255)
Solution of real-world continuum mechanics problems using computational tools commonly used in engineering practice. Develops skills in analysing complexity; selecting a model representation of the physical problem; choosing the correct computational tool to solve the model; designing and executing appropriate numerical experiments; validating, interpreting and communicating simulation results. Advanced solver methods, and modelling of advanced materials such as large-deformation elastic/plastic materials.
Subject: Engineering Science
Prerequisite: BIOMENG 321 or ENGSCI 343
Restriction: ENGSCI 344
2340

ENGSCI 746

: Advanced Modelling and Simulation in Computational Mechanics
2024 Semester Two (1245)
Solution of real-world continuum mechanics problems using computational tools commonly used in engineering practice. Develops skills in analysing complexity; selecting a model representation of the physical problem; choosing the correct computational tool to solve the model; designing and executing appropriate numerical experiments; validating, interpreting and communicating simulation results. Advanced solver methods, and modelling of advanced materials such as large-deformation elastic/plastic materials.
Subject: Engineering Science
Prerequisite: BIOMENG 321 or ENGSCI 343
Restriction: ENGSCI 344
2341

ENGSCI 753

: Computational Techniques in Mechanics and Bioengineering
2021 Semester One (1213)
Theoretical and applied finite element and boundary element methods for static and time dependent problems of heat flow, bioelectricity, linear elasticity and non-linear mechanics.
Subject: Engineering Science
Prerequisite: ENGGEN 131 or equivalent, and 15 points from ENGSCI 311, 313, 314
2342

ENGSCI 753

: Computational Techniques in Mechanics and Bioengineering
2020 Semester One (1203)
Theoretical and applied finite element and boundary element methods for static and time dependent problems of heat flow, bioelectricity, linear elasticity and non-linear mechanics.
Subject: Engineering Science
Prerequisite: ENGGEN 131 or equivalent, and 15 points from ENGSCI 311, 313, 314
2343

ENGSCI 755

: Decision Making in Engineering
2024 Semester Two (1245)
Introduction to techniques for decision making in engineering systems including decision heuristics, simple prioritisation, outranking approaches, analytic hierarchy process, application to group decision making.
Subject: Engineering Science
Prerequisite: ENGSCI 211 or MATHS 250
2344

ENGSCI 755

: Decision Making in Engineering
2023 Semester Two (1235)
Introduction to techniques for decision making in engineering systems including decision heuristics, simple prioritisation, outranking approaches, analytic hierarchy process, application to group decision making.
Subject: Engineering Science
Prerequisite: Departmental approval
2345

ENGSCI 760

: Algorithms for Optimisation
2025 Semester One (1253)
Meta-heuristics and local search techniques such as Genetic Algorithms, Simulated Annealing, Tabu Search and Ant Colony Optimisation for practical optimisation. Introduction to optimisation under uncertainty, including discrete event simulation, decision analysis, Markov chains and Markov decision processes and dynamic programming.
Subject: Engineering Science
Prerequisite: 15 points from COMPSCI 101, ENGGEN 131, MATHS 162, 199, and 15 points from COMPSCI 120, ENGSCI 111, STATS 125
2346

ENGSCI 760

: Algorithms for Optimisation
2024 Semester One (1243)
Meta-heuristics and local search techniques such as Genetic Algorithms, Simulated Annealing, Tabu Search and Ant Colony Optimisation for practical optimisation. Introduction to optimisation under uncertainty, including discrete event simulation, decision analysis, Markov chains and Markov decision processes and dynamic programming.
Subject: Engineering Science
Prerequisite: 15 points from COMPSCI 101, ENGGEN 131, MATHS 162, 199, and 15 points from COMPSCI 120, ENGSCI 111, STATS 125
2347

ENGSCI 760

: Algorithms for Optimisation
2023 Semester One (1233)
Meta-heuristics and local search techniques such as Genetic Algorithms, Simulated Annealing, Tabu Search and Ant Colony Optimisation for practical optimisation. Introduction to optimisation under uncertainty, including discrete event simulation, decision analysis, Markov chains and Markov decision processes and dynamic programming.
Subject: Engineering Science
Prerequisite: COMPSCI 101 or ENGGEN 131
2348

ENGSCI 760

: Algorithms for Optimisation
2022 Semester One (1223)
Meta-heuristics and local search techniques such as Genetic Algorithms, Simulated Annealing, Tabu Search and Ant Colony Optimisation for practical optimisation. Introduction to optimisation under uncertainty, including discrete event simulation, decision analysis, Markov chains and Markov decision processes and dynamic programming.
Subject: Engineering Science
Prerequisite: COMPSCI 101 or ENGGEN 131
2349

ENGSCI 760

: Algorithms for Optimisation
2021 Semester One (1213)
Meta-heuristics and local search techniques such as Genetic Algorithms, Simulated Annealing, Tabu Search and Ant Colony Optimisation for practical optimisation. Introduction to optimisation under uncertainty, including discrete event simulation, decision analysis, Markov chains and Markov decision processes and dynamic programming.
Subject: Engineering Science
Prerequisite: COMPSCI 101 or ENGGEN 131
2350

ENGSCI 760

: Algorithms for Optimisation
2020 Semester One (1203)
Meta-heuristics and local search techniques such as Genetic Algorithms, Simulated Annealing, Tabu Search and Ant Colony Optimisation for practical optimisation. Introduction to optimisation under uncertainty, including discrete event simulation, decision analysis, Markov chains and Markov decision processes and dynamic programming.
Subject: Engineering Science
Prerequisite: COMPSCI 101 or ENGGEN 131