| Summary: | Due to the introduction of modern computing technology to planning, it is anticipated that the techniques for quantitative analysis in planning will be changed radically; the expanding use of model and the increasing importance of inter-city data collection may have an effect in redefining the process of planning itself.
In this thesis, ah effort has been made to investigate the current problems of building and using models in planning so that a methodology, combining several multivariate statistical methods and the modern computation algorithms, is developed for planning analysis and prediction from the comparative point of view. It is hypothesized that simple prediction models can be improved by the use of these comparative techniques.
As a testing mechanism of the proposed methodology,a simple regression model for CBD floor space prediction is devised, and the result shows that the comparative analysis is effective for better prediction. === Applied Science, Faculty of === Community and Regional Planning (SCARP), School of === Graduate
|
|---|
