To learn mathematical techniques in architectural design and research.
To acquire mathematical skills contributing architectural design and research.
Mathematics
✔ Specialist skills | Intercultural skills | Communication skills | ✔ Critical thinking skills | ✔ Practical and/or problem-solving skills |
Lecture.
Course schedule | Required learning | |
---|---|---|
Class 1 | Fundamental of statistical analysis | Learn probability distribution, probability density function, central limit theorem, and confidence interval for analyzing built environmental data. |
Class 2 | Planning of facility location | Learn how to determine the optimum location of facilities. |
Class 3 | Error analysis and hypothesis test | Learn error analysis and hypothesis test for environmental and social data. |
Class 4 | Planning of facility size | Learn how to plan facility size based on the estimated number of users. |
Class 5 | Regression analysis | Learn least square method, regression analysis, correlation coefficient, and multiple regression analysis for environmental and social data. |
Class 6 | Estimation of regional population | Learn how to estimate the regional population. |
Class 7 | Mathematics and physics of heat conduction | Learn differential and difference method, Taylor expansion, and Fourier's law for heat conduction analysis. |
Class 8 | Mathematics and physics of convection | Learn mathematics and physics of convective heat transfer in architectural spaces. |
Class 9 | Estimation of the number of facility users | Learn how to estimate the number of facility users using choice behavior models. |
Class 10 | Basics of land use | building coverage ratio, lot area, road area ratio, floor area ratio, access cost, location requirement, bid rent curve |
Class 11 | Mathematics and physics of convection-diffusion equation | Learn mathematics and physics of convection-diffusion equation by discretizing and solving one-dimensional equation as an example. |
Class 12 | Land use change | revenue and expenses, supply and demand, land price factors, land market |
Class 13 | Application of statistical analysis | Learn the application of statistical analysis using health data in houses |
Class 14 | Land use data and models | land use data, aggregated model, disaggregated model |
To enhance effective learning, students are encouraged to spend approximately 100 minutes preparing for class and another 100 minutes reviewing class content afterwards (including assignments) for each class.
They should do so by referring to textbooks and other course material.
Handout
Handout
Report, Quiz, etc.
N/A