• Journal of Korean Institute of Industrial Engineers
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• v.26 no.3
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• pp.193-199
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• 2000

In many studies, considerable attention has been focussed upon choosing a model which represents underlying process of time series and forecasting the future. In the real world, however, there may be some cases that one model can not reflect all the characteristics of original time series. Under such circumstances, we may get better performance by combining the forecasts from several models. The most popular methods for combining forecasts involve taking a weighted average of multiple forecasts. But the weights are usually unstable. In cases the assumptions of normality and unbiasedness for forecast errors are satisfied, a Bayesian method can be used for updating the weights. In the real world, however, there are many circumstances the Bayesian method is not appropriate. This paper proposes a PNN(Probabilistic Neural Net) approach as a method for combining forecasts that can be applied when the assumption of normality or unbiasedness for forecast errors is not satisfied. In this paper, PNN method, which is similar to Bayesian approach, is suggested as an updating method of the unstable weights in the combination of the forecasts. The PNN method has been usually used in the field of pattern recognition. Unlike the Bayesian approach, it requires no assumption of a specific prior distribution because it gets probabilities by using the distribution estimated from given data. Empirical results reveal that the PNN method offers superior predictive capabilities.

• Journal of the Ergonomics Society of Korea
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• v.32 no.1
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• pp.59-68
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• 2013

Objective: The purpose of this paper is to introduce a task complexity model combining task design aspects and complexity dimensions and to explain an approach to identifying and organizing task complexity factors based on the model. Background: Task complexity is a critical concept in describing and predicting human performance in complex systems such as nuclear power plants(NPPs). In order to understand the nature of task complexity, task complexity factors need to be identified and organized in a systematic manner. Although several methods have been suggested for identifying and organizing task complexity factors, it is rare to find an analytical approach based on a theoretically sound model. Method: This study regarded a task as a system to be designed. Three levels of design ion, which are functional, behavioral, and structural level of a task, characterize the design aspects of a task. The behavioral aspect is further classified into five cognitive processing activity types(information collection, information analysis, decision and action selection, action implementation, and action feedback). The complexity dimensions describe a task complexity from different perspectives that are size, variety, and order/organization. Combining the design aspects and complexity dimensions of a task, we developed a model from which meaningful task complexity factors can be identified and organized in an analytic way. Results: A model consisting of two facets, each of which is respectively concerned with design aspects and complexity dimensions, were proposed. Additionally, twenty-one task complexity factors were identified and organized based on the model. Conclusion: The model and approach introduced in this paper can be effectively used for examining human performance and human-system interface design issues in NPPs. Application: The model and approach introduced in this paper could be used for several human factors problems, including task allocation and design of information aiding, in NPPs and extended to other types of complex systems such as air traffic control systems as well.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2006.10a
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• pp.144-153
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• 2006

In order to take TC forecasts from different observatories into consideration, and make quantitative assessment and analysis for avoiding TC routes from the view of safety and cost, a new safe-economic decision making method of TC avoidance routing on ocean was put forward. This model is based on combining forecast of TC trace based on neural networks, technical method to determine the future TC wind and wave fields, technical method of fuzzy information optimization, risk analysis theory, and meteorological-economic decision making theory. It has applied to the simulation of MV Tianlihai's shipping on ocean. The result shows that the model can select the optimum plan from 7 plans, the selected plan is in accordance with the one selected by experienced captains.

• Coupled systems mechanics
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• v.11 no.1
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• pp.1-14
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• 2022

The key parameter that affects the consolidation process of soil is the coefficient of permeability. The common assumption in the consolidation analysis is that the coefficient of permeability is porosity-dependent. However, various authors suggest that the strain-dependency of the coefficient of permeability should also be taken into account. In this paper, we present results of experimental and numerical analyses, with an aim to determine the strain-dependency of the coefficient of permeability. We present in detail both the experimental procedure and the finite element formulation of the two-dimensional axisymmetric numerical model of the oedometer test (standard and modified). We perform a set of experimental standard and modified oedometer tests. We use these experimental results to validate our numerical model and to define the model input parameter. Finally, by combining the experimental and numerical results, we propose the expression for the strain-dependent coefficient of permeability.

• Journal of Information Technology Applications and Management
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• v.17 no.2
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• pp.187-205
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• 2010

This study takes a holistic approach to understand the diffusion of IPTV services by combining the adoption-diffusion model and the use-diffusion model of innovation. IPTV service, a leading digital converged application coupling media content with telecommunications, has been recently launched commercially in Korea. We created a structural model of adoption-diffusion, using the perceived easeof-use and usefulness of TAM(Technology Acceptance Model) as mediating variables, and a structural model of use-diffusion, with the rate of use and the variety of use as mediating variables. To empirically analyze these models, non-users of IPTV were surveyed using the adoption-diffusion model to identify factors influencing their intention to subscribe to the service. Meanwhile, users of IPTV were surveyed using the use-diffusion model to determine the factors that influence their satisfaction with the service and their intention to re-use it. Under the adoption-diffusion model, we found that trialability, household innovativeness and perceived risk were the determinants of user satisfaction with IPTV, and perceived ease-of-use, the mediating factors. Under the use-diffusion model, complementarity and communication were shown to be the determinants of users' satisfaction with IPTV, and variety of use, the mediating factor. We also found that consumers' intention to re-use IPTV was strongly influenced by its relative advantage and perceived risk.

• Journal of Advanced Marine Engineering and Technology
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• v.40 no.8
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• pp.721-725
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• 2016

This paper reviews the analysis of a given scenario according to the Hybrid Model, and why accident causation models are necessary in casualty investigations. The given scenario has been analyzed according to the Hybrid Model using its main five components, fallible decisions, line management, psychological precursors to unsafe acts, unsafe acts, and inadequate defenses. In addition, the differences between the SHEL and the Hybrid Model, and the importance of a safety barrier during an accident investigation, are shown in this paper. One unit of SHEL can be linked with another unit of SHEL. However, it cannot be used for the analysis of an accident. Therefore, we must use an accident causation model, which can be a Hybrid Model. This can explain the "How" and "Why" of accident, so it is a suitable model for analyzing them. During an accident investigation, the reason we focus on a safety barrier is to create another safety barrier or to change an existing safety barrier if that barrier fails. Hence, the paper shows how a sea accident can be investigated, and we propose a preventive way of avoiding the accident through combining the methods of different models for the future.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.330-330
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• 2002

The combination of Multi-Beam Echo Sounder swath bathymetry and high-resolution towed Sidescan sonar provides a powerful method of examination about hydrographic survey results. In this paper, we investigate the fast method of 3D bathymetric reconstruction with the Digital Sidescan sonar(Benthos SIS 1500) and Shallow Multi-Beam Echo Sounder(Reson Seabat 8125). The Seabat 8125 is a 455KHz high resolution focused Multibeam echo sounder(MBES) system which measures the relative water depth across a wide swath perpendicular to a vessel's track. The Benthos SIS1500 is a chirp(nominal fq. 200KHz) sonar which map the topographical features & sediment texture of ocean bottom using backscattered amplitude. We generates the very large 3D bathymetric texture mapping model with the Helical System's HHViewer and describes additional benefits of combining MBES and Sidescan Sonar imagery, the removal of geometric distortions in the model and a deterministic sounding noise.

• The Korean Journal of Applied Statistics
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• v.25 no.2
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• pp.251-259
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• 2012

This paper applies forecasting models such as ARIMA, Holt-Winters and AR-GARCH models to analyze daily tourism data in Korea. To evaluate the performance of the models, we need single and double seasonal models that compare the RMSE and SE for a better accuracy of the forecasting models based on Armstrong (2001).

• Journal of Korean Society of Steel Construction
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• v.8 no.3 s.28
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• pp.97-105
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• 1996

A Stochastic line source model is developed to simulate the seismic wave field generated during the rupture propagation process along a fault plane of which length is much larger than its width. The fault plane is assumed to consist of randomly distributed slip zones and barriers and each slip zone is modeled as a point source. By combining the newly developed source model with wave propagation analysis method in a layered 3-D visco-elastic half space, synthetic seismograms are obtained. The calculated accelerograms due to vertical dip slip and strike slip line sources are presented.

• The Transactions of the Korea Information Processing Society
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• v.7 no.4
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• pp.1150-1159
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• 2000

This paper presents an automatic text categorization model that improves the accuracy by combining statistical and knowledge-based categorization methods. In our model we apply knowledge-based method first, and then apply statistical method on the text which are not categorized by knowledge-based method. By using this combined method, we can improve the accuracy of categorization while categorize all the texts without failure. For statistical categorization, the vector model with Inverted Category Frequency (ICF) weighting is used. For knowledge-based categorization, Phrasal Patterns and Keyword Sets are introduced to represent sentence patterns, and then pattern matching is performed. Experimental results on new articles show that the accuracy of categorization can be improved by combining the tow different categorization methods.