• The Journal of Society for e-Business Studies
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• v.24 no.1
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• pp.91-103
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• 2019

An accurate prediction on near-future cash flows plays an important role for a company to attenuate the shortage risk of cash flow by preparing a plan for future investment in advance. Unfortunately, there exists a high level of uncertainty in the types of transactions that occur in the form of receivables in inter-company transactions, unlike other types of transactions, thereby making the prediction of cash flows difficult. In this study, we analyze the trend of cash flow related to account receivables that may arise between firms, by using a stochastic approach. In particular, we utilize Variable Order Markov (VOM) model to predict how future cash flows will change based on cash flow history. As a result of this study, we show that the average accuracy of the VOM model increases about 12.5% or more compared with that of other existing techniques.

• Journal of the Korea Institute of Building Construction
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• v.18 no.6
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• pp.611-619
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• 2018

The researches have only conducted regarding construction safety management and risk on interior construction site(workers) and is insufficient about the exterior construction site(third party). As a result, ordinary people who were near construction sites have injured and hold a negative view when they think about the construction industry because construction industry have been exposed to them having a high accidents rate through media. In addition, the importance of industrial disaster prevention is emphasized at this point in time, the overall safety management system should be constructed with considering construction site external(third human) for improving the negative image of the construction industry among ordinary people. Therefore, the objective of this study is to develop the quantification model of human accident utilizing the insurance claim payout occurred construction site exterior(third party). In the future, it can be used as a reference for developing the safety management checklist in construction site interior exterior and development for forecasting control system of human accident.

• Journal of the Korea Institute of Building Construction
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• v.18 no.6
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• pp.595-602
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• 2018

Network-based scheduling methods can be classified into CPM method and PERT method. In the network scheduling chart, critical path can be estimated by performing the forward calculation and the backward calculation though the paths in the network chart. In PERT method, however, it is unreasonable to simply estimate the critical path by adding the sum of the activity durations in a specific path, since it does not incorporate probabilistic concept of PERT. The critical path of a PERT network can change according to the target period and deviation, and in some cases, the expected time of the critical path may not be the path with longest expected time. Based on this concept, this study proposes a technique to derive the most-likely critical path by comparing the sum of estimated time with the target time. It also proposes a method of systematically deriving all alternate paths for a network of repetitive activities. Case studies demonstrated that the most-likely critical path is not a fixed path and may vary according to the target period and standard deviation. It is expected that the proposed method of project duration forecasting will be useful in construction environment with varying target date situations.

• Journal of Korea Water Resources Association
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• v.55 no.9
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• pp.657-668
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• 2022

With the occurrence of localized heavy rain while river flow has increased, both flow and rainfall cause riverside flood damages. As the degree of damage varies according to the level of social and economic impact, it is required to secure sufficient forecast lead time for flood response in areas with high population and asset density. In this study, the author established a flood risk matrix using ensemble rainfall runoff modeling and evaluated its applicability in order to increase the damage reduction effect by securing the time required for flood response. The flood risk matrix constructs the flood damage impact level (X-axis) using flood damage data and predicts the likelihood of flood occurrence (Y-axis) according to the result of ensemble rainfall runoff modeling using LENS rainfall data and as well as probabilistic forecasting. Therefore, the author introduced a method for determining the impact level of flood damage using historical flood damage data and quantitative flood damage assessment methods. It was compared with the existing flood warning data and the damage situation at the flood warning points in the Taehwa River Basin and the Hyeongsan River Basin in the Nakdong River Region. As a result, the analysis showed that it was possible to predict the time and degree of flood risk from up to three days in advance. Hence, it will be helpful for damage reduction activities by securing the lead time for flood response.