Methods of Transport Prognostics

1. Exploratory data analysis – basic concepts, frequencies, measures of mean.
2. Exploratory data analysis – measures of variability, identification of outliers, analysis of large random samples, graphical representation of random samples.
3. Elementary description of dependencies between random variables, testing for independence in contingency tables.
4. Correlation analysis – Pearson’s correlation coefficient, testing linear independence, Spearman’s correlation coefficient.
5. Regression analysis – basic concepts, basic types of regression functions, the least squares method and its application in estimating linear regression parameters, linear regression in Excel.
6. Regression Analysis – other types of regression models and their implementation in Excel, multiple regression and its application in Excel.
7. Time Series – basic concepts, classification of time series, introduction to time series modeling.
8. Time Series – linear trend, parabolic trend, exponential trend.
9. Time series – modified exponential trend, logistic curve, Gompertz curve.
10. Time series – criteria for trend selection.
11. Time series – adaptive approaches to time series modeling.
12. Four-phase traffic forecasting model – introduction to the topic, calculation of projected traffic volumes – use of regression analysis, specific momentum methods.
13. Four-phase traffic forecasting model – determination of inter-area relationships – analogical methods and synthetic methods, division of traffic volume, allocation to the network.