• 농촌계획
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• 제14권2호
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• pp.55-64
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• 2008

This study aims to analyze the sensitivity of WSM(weighted scenario method)-AHP method according to variation of nonlinear exponent for accessibility criteria, which are used to make urbanization potential maps with the optimal weighting value for multiple criteria in grid-based GIS technique. Besides this study tried to develop WSM-AHP2 which is simplified by using rank of the potential value for each scenario. The two methods were applied to the test area, Suwon city located south area of Seoul, with time series land-use maps of 1986 and 1996. The evaluation system of urbanization potential have 7 criteria including 6 accessibility criteria. The results of WSM-AHP2, the optimal weighting values and their corresponding potential maps, have almost similar with those of WSM-AHP. In the application of CA(cellular automata) model for expansion of urbanized area using the three potential maps by WSM-AHP, WSM-AHP2, and specialists's AHP evaluation, it also showed that the accuracy of simulation for actual urban area is the highest in the potential map of WSM-AHP, followed by WSM-AHP2 and specialists's AHP evaluation. From the results of this study, WSM-AHP and simplified WSM-AHP2 will be used to generate the optimal potential maps for land-use planning in urban fringe area.

• 국제학술발표논문집
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• The 3th International Conference on Construction Engineering and Project Management
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• pp.700-706
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• 2009

Bridges are vital components of any road network which demand crucial and timely decision-making for Maintenance, Repair and Rehabilitation (MR&R) activities. Bridge Management Systems (BMSs) as a decision support system (DSS), have been developed since the early 1990's to assist in the management of a large bridge network. Historical condition ratings obtained from biennial bridge inspections are major resources for predicting future bridge deteriorations via BMSs. Available historical condition ratings in most bridge agencies, however, are very limited, and thus posing a major barrier for obtaining reliable future structural performances. To alleviate this problem, the verified Backward Prediction Model (BPM) technique has been developed to help generate missing historical condition ratings. This is achieved through establishing the correlation between known condition ratings and such non-bridge factors as climate and environmental conditions, traffic volumes and population growth. Such correlations can then be used to obtain the bridge condition ratings of the missing years. With the help of these generated datasets, the currently available bridge deterioration model can be utilized to more reliably forecast future bridge conditions. In this paper, the prediction accuracy based on 4 and 9 BPM-generated historical condition ratings as input data are compared, using deterministic and stochastic bridge deterioration models. The comparison outcomes indicate that the prediction error decreases as more historical condition ratings obtained. This implies that the BPM can be utilised to generate unavailable historical data, which is crucial for bridge deterioration models to achieve more accurate prediction results. Nevertheless, there are considerable limitations in the existing bridge deterioration models. Thus, further research is essential to improve the prediction accuracy of bridge deterioration models.