Nao Sugiki
Toyohashi University of Technology
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Featured researches published by Nao Sugiki.
Transportation Research Record | 2011
Noriko Otani; Nao Sugiki; Kazuaki Miyamoto
Microsimulation models of land use characterize attributes of a household and its location, referred to as microdata in this study. However, methods for evaluating the goodness of fit between estimated and observed sets of agent-based microdata have not been investigated extensively. Although the attributes of a household include various items, such as the relationship with the household head and ages of the members, housing type and spatial location, number of cars owned, and income, the attributes can be classified into general categories. The objective of the present study is to develop a goodness-of-fit evaluation method for agent-based household microdata sets composed of generalized attributes. First, a distance measure between the estimated and observed microdata for each household is defined. In this definition a generalized scheme is introduced, whereby attributes are structured by the household composition, attributes of the member, and attributes of the household as a whole. The goodness of fit is measured on the basis of the minimum sum of distances for all households in the study area. The calculation cannot be carried out with just a conventional algorithm for microdata of a typical size because the number of calculations increases in proportion to the factorial (N!) of the number (N) of agents. Therefore, a genetic algorithm, especially one using symbiotic evolution, is developed to solve the problem. The effectiveness of the method in regard to accuracy and calculation feasibility is confirmed by using person trip survey data for the Sapporo metropolitan area in Japan.
Archive | 2013
Kazuaki Miyamoto; Nao Sugiki; Noriko Otani; Varameth Vichiensan
Land-use microsimulation is becoming an indispensable function in a planning support system for sustainable urban development because it provides the detailed information necessary for decision making on emerging issues at the household or firm level. In land-use microsimulations, there are two approaches for estimating base-year micro-data: cell-based population synthesis, which generally uses the iterative proportional fitting method, and agent-based methods. This chapter compares these two methods qualitatively and quantitatively. The qualitative comparison shows that neither one is superior in every aspect. The cell-based method is preferred when the microsimulation deals with data sufficiently simple, while the agent-based method is preferred when accurate and/or numerous micro-data attributes are demanded. Similarly, the quantitative comparison based on a goodness-of-fit evaluation does not show a single superior method for all applications. These findings suggest a way for selecting a better method based on the conditions of the microsimulation model and the purpose of its application.
Transportation Research Record | 2012
Noriko Otani; Nao Sugiki; Varameth Vichiensan; Kazuaki Miyamoto
Land use microsimulation requires the preparation of a set of microdata for the base year. Most existing procedures used for the synthesis of population data are based on the iterative proportional fitting method, in which the number of individuals in each cell of the cross-classification table is estimated. Such a procedure is referred to as the cell-based approach in this study. The approach is based on predefined categories of individuals. Originally, however, these individuals have continuous attributes. Therefore, a different type of categorization would yield a different classification table, which would change the end results of the analysis. In this paper, this phenomenon is referred to as the modifiable attribute cell problem (MACP). It is similar to the modifiable area unit problem that arises when spatial data are aggregated into zones. This paper addresses MACP and proposes a method to determine the best combination of the categories. The solution of MACP is considered to be the minimization of the number of cells in a table with respect to the key output variable that has been defined and used as an evaluation criterion. Because of the computational difficulty resulting from the combination explosion, symbiotic evolution, which is a kind of genetic algorithm, is used. Finally, a case study is presented for the Sapporo metropolitan area of Japan.
annual conference on computers | 2017
Nao Sugiki; Kazuaki Miyamoto; Akinari Kashimura; Noriko Otani
During the past several decades, many new towns have emerged in suburbs along new railway lines in Japan. Numerous problems in those towns are emerging as their population age. This study aimed to build a micro-simulation model of households to estimate residents’ assessments of quality of life in a suburban new town of a metropolis. Approximately 1500 households were sampled to collect survey data. Using census data and the survey data, base-year household microdata were estimated using the agent-based synthesis method. The survey data provided information on household histories after taking up residence in the present house. A microsimulation model was built using the household history data and simulations were performed to predict household transitions in the study area in five-year increments between 2015 and 2045.
Asian transport studies | 2012
Nao Sugiki; Varameth Vichiensan; Noriko Otani; Kazuaki Miyamoto
11th World Conference on Transport ResearchWorld Conference on Transport Research Society | 2007
Kazuaki Miyamoto; Varameth Vichiensan; Nao Sugiki; Keiichi Kitazume
Journal of the Eastern Asia Society for Transportation Studies | 2005
Nao Sugiki; Kazuaki Miyamoto; Makoto Inomoto; Toyohiro Mori
Transportation Research Board 89th Annual MeetingTransportation Research Board | 2010
Kazuaki Miyamoto; Nao Sugiki; Noriko Otani; Varameth Vichiensan
10th World Conference on Transport ResearchWorld Conference on Transport Research SocietyIstanbul Technical University | 2004
Nao Sugiki; Kazuaki Miyamoto
Procedia Engineering | 2017
Katia Andrade; Hayato Nakano; Nao Sugiki; Toru Tamura