Quantitative Techniques for Infrastructure Systems Analysis

Objective: To provide knowledge of quantitative techniques with application potential for transportation system.

Contents: 

1. Modelling and Simulation: Model Classification, Mathematical; Physical and Analog models, steps involved in simulation, Monte Carlo simulation, validation and verification of simulation models.

2. Curve Fitting: Method of least squares, curvilinear regression, Multiple regression, checking adequacy of model, correlation, multiple linear regression (Matrix Notation)

3. Queuing Theory: General structure, operating characteristics, deterministic queuing model, probabilistic queuing models, and simulation of queuing system.

4. Multivariate Data Analysis: Vectors and Matrices, Simple estimate of centroid, standard deviation, dispersion, variance and co-variance, correlation matrices, principal component analysis.

5. Forecasting Models: Moving averages, exponential smoothening, trend projections, causal models, time series analysis of vehicle growth & accidents.

6. Design of Experiments: General principles, completely randomized design, randomized block designs, latin square design, analysis of co-variance.

7. Neural Networks: Basic concepts; neural network architecture, back propagation networks

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