Design and Analysis of Computer Experiments, Structural Equation Modeling and Wavelet Analysis of Daily Flows
This research proposal has four main objectives: 1) to investigate the use of recently developed design and analysis of computer experiments methodology for the surrogate modeling of complex environmental/civil engineering models. If successful, this surrogate model will reduce considerably the computing efforts for subsequent uncertainty, sensitivity, and Monte-Carlo analyses of complex computer models; 2) to investigate the possibility of using the response surface methodology techniques in extracting an explicit model from an artificial neural network. The absence of an explicit model associated with the ANNs makes it difficult for the networks to be reproduced and therefore not easily integrated to form coupled models for example. Explicit model extraction from various ANNs ranging in complexly will be investigated. The applicability and limitations of RSM will be comprehensively explored, (3) to investigate the application of structural equation modeling (SEM) for regional flow analysis and environmental modeling.
The rapid progress made in terms of theory and software development warrants a new look at this method that has enjoyed exponential growth in usage in many fields of study. Regional flow analysis data and environmental monitoring data from Newfoundland will be used as case studies. The proposed method will also be compared to currently used methods; and 4) to investigate the application of wavelets analysis methods for daily river flow modeling. Wavelets has been found to be especially useful for analyzing time series with non-stationary or transitory characteristics such as drifts, trends, abrupt changes, self-similarity, and beginnings and ends of events, much like daily river flow series.
This proposal will compare the proposed method with traditional methods. The results of this research will be especially useful to engineers involved in hydrological and environmental modeling. It will provide more efficient tools to tackle the increasingly complex problems that engineers face.