Numerical Methods & Artificial Intelligence in Geotechnical Engg
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Follow on Instagram for UpdatesNumerical Methods & Artificial Intelligence in Geotechnical Engg Syllabus — Unit-wise Content
The official GTU curriculum for Numerical Methods & Artificial Intelligence in Geotechnical Engg (subject code ME01076031) as prescribed for GE · Semester 1 divides the course into 4 units, covering 30 listed topics. The unit-wise breakdown below is read from the GTU syllabus document for this subject code, so you can check what the course actually covers before deciding which papers to attempt.
Download the official syllabus PDF (ME01076031)Unit 1 Introduction to variational calculus and Various Numerical Methods
- Linear equations and eigen value problems
- Accuracy of approximate calculations
- Nonlinear equations
- differentiation and evaluation of single and multiple integrals
- initial and boundary value problems by finite difference method
- Newton’s method
- variation and weighted residual methods
Unit 2 Finite Element Method
- Finite element descritization
- displacement models
- Natural and general co-ordinate systems
- Derivation of properties of one and two dimensional elements
- Isoparametric elements
- Stiffness matrix and load vectors
- Numerical integration
- Assembly and solution techniques
Unit 3 Machine Learning Basics
- Data Collection
- Data Management
- Big data
- taxonomy of machine learning algorithms
- Supervised Learning: Classification – Bayesian Classifier
- K-nearest Neighbours
- Regression- Linear Regression
- Multivariate Regression
- Logistic regression
- Support Vector Machine (SVM) Algorithm
- Unsupervised Learning: Clustering- K-means clustering algorithm and Hierarchical clustering algorithm
- Reinforcement Learning: Q-Learning algorithm
Unit 4 Introduction- Classification of artificial intelligence-expert systems-
- artificial neural networks basic concepts-uses in functional approximation and optimization applications in the design and analysis
- building construction
- Fuzzy logic-basic concepts-problem formulation using fuzzy logic-applications