• Journal of Korea Technology Innovation Society
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• v.16 no.1
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• pp.303-322
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• 2013

A relevance of supporting business of technology financing for technologically innovative SMEs is strongly required for its continuous expansion and development. This study analyzes empirically whether the selection of recipient firms from technology financing have been performed in accordance with its objectives and purposes. Results show that the probability of receiving technology financing is more likely to increase with higher technology rankings and higher operating income ratio. On the other hand, the probability of obtaining financing might be decreased gradually, as the size of capital and age of the firm are increasing. Results also show that technology rankings and firm's major characteristics are found to affect significantly on the decision-making of technology financing. Several useful comments are suggested to improve the relevance of the technology financing since the correct classification rate, which explains the appropriateness of the model, is not at high level. In addition, technology rankings are not uncorrelated with the amount of financing in regression analysis. These research results will contribute to ensure the appropriateness and credibility of the technology financing decision-making.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.3
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• pp.1014-1020
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• 2012

This paper focuses on the development of a supporting S/W tool that can minimize designer's manual operations and errors in metal mold design based on a 3D solid model. The scope in this work includes the offset surface modeling, the computation of the padding force, the generation of material table, the decision of hole position, the estimation of the size of raw material, which are the essential parts of press die and mold design in automotive industry. The proposed system has been developed as a plug-in type using Pro/E API and Visual C++ in order to put the system into the menu functions of Pro/E which is one major 3D CAD systems in the manufacturing industry.

• Journal of the Korea Society for Simulation
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• v.29 no.4
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• pp.85-94
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• 2020

In determining the feasibility of planning and launching railway transportation projects, various decision-making processes are essentially required. LCC(Life Cycle Cost) value including total construction cost and operation cost is estimated in approximation Model with rough guideline. In this study, modeling and simulation-based analysis method is proposed to support the decision making process of railroad transportation and derivation of LCC. Firstly, cost analysis model was constructed by collecting various existing rail transportation business data to enable analyze based on numerical data, and the result were analyzed by DOE(Design Of Experiments) and RSM (Response Surface Method) simulation. Professional commercial software tools were used for effective model construction and simulation. In order to verify the research results, the actual railroad transportation projects were selected, and the results of the analysis were compared.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.34 no.2
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• pp.645-654
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• 2014

PMS (Pavement Management System) of National highways in Korea has used HDM (Highway Development and Management)-4 developed by World Bank for decision-making for maintenance and rehabilitation of pavements. However using HDM-4 is not appropriate in Korea because HDM-4 requires excessive input factors for analysis and economic analysis models loaded in HDM-4 are not suitable for Korean circumstances. Thus this study aims development of decision-making system for effective pavement management with reflecting Korean circumstances. Moreover this study proposed to define component of system, deterioration models, and basic units for component, and to analyze characteristics of component of system, and also to develop optimal decision-making system. The decision-making system for PMS mainly consists of 1) DB of highways, traffics, and socio-economic index, 2) pavement deterioration model, 3) speed prediction models by pavement conditions, 4) economic evaluation models, and 5) decision-making supporting system. Also this study provided analysis results in case studies for system verifications. However pavement deterioration models considering future probabilistic characteristic and index of decision-making are needed to develop for a further study.

• Journal of the Architectural Institute of Korea Planning & Design
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• v.33 no.12
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• pp.13-18
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• 2017

Recently, the form of traditional families has been disintegrated due to low birthrate, aging, declining marriage, individualism, etc. In particular, the number of single households has increased due to the shift to a low-growth advanced economic structure, women's social participation, diversification of lifestyles, and so on. According to the National Statistical Office, the number of single households living alone by 2015 is estimated to be about 5,060,000 households, which is estimated to account for 34.3% of all households, which has greatly increased compared with about 660,000 (6.9%) in 1985. However, the housing market has not been able to respond to such social changes. Therefore, in this research, we presented a plan to visualize the public data of single household in Seoul city and prediction result of occupancy shape for the purpose of supporting decision making of single household consumers.

• Journal of Information Processing Systems
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• v.17 no.4
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• pp.721-736
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• 2021

For the mobile edge computing (MEC) system supporting dense network, a joint allocation algorithm of computing and communication resources based on reinforcement learning is proposed. The energy consumption of task execution is defined as the maximum energy consumption of each user's task execution in the system. Considering the constraints of task unloading, power allocation, transmission rate and calculation resource allocation, the problem of joint task unloading and resource allocation is modeled as a problem of maximum task execution energy consumption minimization. As a mixed integer nonlinear programming problem, it is difficult to be directly solve by traditional optimization methods. This paper uses reinforcement learning algorithm to solve this problem. Then, the Markov decision-making process and the theoretical basis of reinforcement learning are introduced to provide a theoretical basis for the algorithm simulation experiment. Based on the algorithm of reinforcement learning and joint allocation of communication resources, the joint optimization of data task unloading and power control strategy is carried out for each terminal device, and the local computing model and task unloading model are built. The simulation results show that the total task computation cost of the proposed algorithm is 5%-10% less than that of the two comparison algorithms under the same task input. At the same time, the total task computation cost of the proposed algorithm is more than 5% less than that of the two new comparison algorithms.

• Journal of Distribution Science
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• v.20 no.6
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• pp.1-10
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• 2022

Purpose: This research proposes a new modified Recency-Frequency-Monetary (RFM) model by extending the model with spatial analysis for supporting decision-makers in discovering the promotional target market. Research design, data and methodology: This quantitative research utilizes data-mining techniques and the RFM model to cluster a university's provider schools. The RFM model was modified by adapting its variables to the university's marketing context and adding a district's potential (D) variable based on heatmap analysis using Geographic Information System (GIS) and K-means clustering. The K-prototype algorithm and the Elbow method were applied to find provider school clusters using the proposed RFM-D model. After profiling the clusters, the target segment was assigned. The model was validated using empirical data from an Indonesian university, and its performance was compared to the Customer Lifetime Value (CLV)-based RFM utilizing accuracy, precision, recall, and F1-score metrics. Results: This research identified five clusters. The target segment was chosen from the highest-value and high-value clusters that comprised 17.80% of provider schools but can contribute 75.77% of students. Conclusions: The proposed model recommended more targeted schools in higher-potential districts and predicted the target segment with 0.99 accuracies, outperforming the CLV-based model. The empirical findings help university management determine the promotion location and allocate resources for promotional information distribution and student recruitment.

• Journal of Korean Society for Quality Management
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• v.51 no.3
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• pp.363-379
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• 2023

Purpose: The main objective of this research is to construct an AI-based Composite Supplementary Index (ACSI) model to achieve accurate predictions of the Composite Index of Business Indicators. By incorporating various economic indicators as independent variables, the ACSI model enables the prediction and analysis of both the leading index (CLI) and coincident index (CCI). Methods: This study proposes an AI-based Composite Supplementary Index (ACSI) model that leverages diverse economic indicators as independent variables to forecast leading and coincident economic indicators. To evaluate the model's performance, advanced machine learning techniques including MLP, RNN, LSTM, and GRU were employed. Furthermore, the study explores the potential of employing deep learning models to train the weights associated with the independent variables that constitute the composite supplementary index. Results: The experimental results demonstrate the superior accuracy of the proposed composite supple- mentary index model in predicting leading and coincident economic indicators. Consequently, this model proves to be highly effective in forecasting economic cycles. Conclusion: In conclusion, the developed AI-based Composite Supplementary Index (ACSI) model successfully predicts the Composite Index of Business Indicators. Apart from its utility in management, economics, and investment domains, this model serves as a valuable indicator supporting policy-making and decision-making processes related to the economy.

• Journal of Korean Society of Rural Planning
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• v.9 no.4 s.21
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• pp.43-51
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• 2003

This study aims to integrate the simulation models for rural settlement planning (SimRusep) in the district level (Myon) area of rural counties. The SimRusep, which has two modules of key villages selection and spatial planning for the selected villages, consists of four sub-models such as the spatial location-allocation model of center villages (SLAMCV), the potential centrality evaluation model (PCEM), the land use planning model (LUPM), and the 3-dimensional spatial planning modeller (3DSPLAM). Basically, map data of the integrated system which can be operated on the UNIX environment is inputted and treated using GIS (ARC/INFO) and then its village planning results is graphically presented on the AutoCAD. In order to verify the practical applicabilities of the SimRusep, an administrative area, Ucheon-myun, HoengSung-gun, KangWon-do, was selected as a case study area. It was well operated in the strategic application trials considering application of each sub-model in the study area. The operation results of the SimRusep showed the possibilities of realtime simulation from the selection of key village to its final stereoscopic presentation of planned results. Alternative village plan proposals can be swiftly drafted, which means very practical support for decision making process and public participation.

• Journal of KIISE:Computing Practices and Letters
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• v.6 no.1
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• pp.1-10
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• 2000

Spatial analysis in GIS provides an important way that helps the end-users decision-making. For such a reason, query model for analysis should be able to support the users view conceptually in constructing query statements. The traditional approaches in design of query model used to extend the functionality of model that basically designed for manipulation of attribute-operations by appending operators for spatial operations to the query statements of model. However, by the reason of spatial operation's characteristics that are different from those of attribute operations In nature, the structures of query statements in previous approaches are unnatural, inconsistent, and therefore those query models in previous approaches are not able to support the users view in retrieving analysis. In this paper, we proposed the methodology for constructing of user query and internal processing this query based on object-oriented paradigm, in the view of spatial operations by using the basic concept that spatial query is a methodology for spatial analysis. In addition, we presented a strong possibility of designing spatial query model that might actively have interaction with its user by implementing CIW(Class-Information Window) query interface corresponded with the methodology proposed in this paper.