Undergraduate Certificate in Time Series Analysis in Civil Engineering
-- ViewingNowThe Undergraduate Certificate in Time Series Analysis in Civil Engineering is a crucial course designed to equip learners with essential skills in analyzing and forecasting civil engineering systems. This program focuses on time-dependent data, a critical aspect of infrastructure planning and management.
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โข Time Series Analysis Fundamentals: Introduction to time series analysis, time domain representation, stationarity, autocorrelation, spectral analysis.
โข Time Series Models: Autoregressive (AR), moving average (MA), autoregressive moving average (ARMA), autoregressive integrated moving average (ARIMA) models, seasonal models.
โข Model Selection and Evaluation: Model selection criteria, information criteria, Akaike information criterion (AIC), Bayesian information criterion (BIC), residual analysis.
โข Time Series Forecasting: Box-Jenkins approach, forecasting with ARIMA models, seasonal forecasting, exponential smoothing state space models (ETS), combining forecasts.
โข Spectral Analysis: Fourier transform, periodogram, spectral density estimation, spectral density functions.
โข State Space Models: Introduction to state space models, Kalman filter, smoothing algorithms.
โข Multivariate Time Series Analysis: Vector autoregression (VAR), vector error correction models (VECM), impulse response functions, forecast error variance decomposition.
โข Time Series Analysis in Civil Engineering Applications: Time series analysis in transportation engineering, hydrology, geotechnical engineering, structural engineering, and infrastructure management.
โข Case Studies in Time Series Analysis: Real-world civil engineering case studies using time series analysis techniques.
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