Bankruptcy Prediction Modeling Using Multiple Neural Network Models

November 5, 2010

Shin, K. Lee, K., Bankruptcy Prediction Modeling Using Multiple Neural Network Models, Lecture Notes in Artificial Intelligence 3214:668–674, September, 2004. – SCIE, ISSN:0302-9743

Abstract

The primary goal of this paper is to get over the limitations of single neural network models through model integration so as to increase the accuracy of bankruptcy prediction. We take the closeness of the output value to either 0 or 1 as the models confidence in its prediction as to whether or not a company is going to bankrupt. In case where multiple models yield conflicting prediction results, our integrated model takes the output value of the highest confidence as the final output. The output of the confidence-based integration approach significantly increases the prediction performance. The results of composite prediction suggest that the proposed approach will offer improved performance in business classification problems by integrating case-specific knowledge with the confidence information and general knowledge with the multi-layer perceptrons generalization capability.

Filed under Knowledge Management and Engineering, Other Publications

Neuro-genetic Approach for Bankruptcy Prediction Modeling

November 5, 2010

Shin, K. Lee, K., Neuro-genetic Approach for Bankruptcy Prediction Modeling, Lecture Notes in Artificial Intelligence 3214:646–652, September, 2004. – SCIE, ISSN:0302-9743.

Abstract  

Artificial neural network (ANN) modeling has become the dominant modeling paradigm for bankruptcy prediction. To further improve the neural networks prediction capability, the integration of the ANN models and the hybridization of ANN with relevant paradigms such as evolutionary computing has been demanded. This paper first attempted to apply neurogenetic approach to bankruptcy prediction problem for finding optimal weights and confirmed that the approach can be a good methodology though it currently could not outperform the backpropagation learning algorithm. The result of this paper shows a possibility of neurogenetic approach to bankruptcy prediction problem since the simple neurogenetic approach produced a meaningful performance.

Filed under Knowledge Management and Engineering, Other Publications

Support Vector Machines Approach to Pattern Detection in Bankruptcy Prediction and its Contingency

November 5, 2010

Shin, K., Lee, K., Kim, H., Support Vector Machines Approach to Pattern Detection in Bankruptcy Prediction and its Contingency, Lecture Notes in Computer Science 3316:1254-1259, November, 2004.  – SCIE ISSN:0302-9743. pdf

Abstract

This study investigates the effectiveness of support vector machines (SVM) approach in detecting the underlying data pattern for the corporate failure prediction tasks. Back-propagation neural network (BPN) has some limitations in that it needs a modeling art to find an appropriate structure and optimal solution and also large training set enough to search the weights of the network. SVM extracts the optimal solution with the small training set by capturing geometric characteristics of feature space without deriving weights of networks from the training data. In this study, we show the advantage of SVM approach over BPN to the problem of corporate bankruptcy prediction. SVM shows the highest level of accuracies and better generalization performance than BPN especially when the training set size is smaller.

Filed under Knowledge Management and Engineering, Other Publications

A Cross-National Market Segmentation of Online Game Industry Using SOM

November 4, 2010

Lee, S., Suh, Y., Kim, J., Lee, K, A Cross-National Market Segmentation of Online Game Industry Using SOM, Expert Systems with Applications, 27:559-570, 2004. – SCIE, ISSN: 0957-4174. pdf

Abstract

To compete successfully in today’s global online game markets, a cross-national analysis for market segmentation is becoming a more important issue, by which companies are able to understand their domestic and foreign loyal customers and concentrate their limited resources into the target customers. However, previous research methodologies for market segmentation were difficult to be conducted on a cross-national analysis because they were performed within a nation. Additionally, the traditional clustering methodologies have not provided a unique clustering nor determined the precise number of clusters. The purpose of our research is to develop a new methodology for cross-national market segmentation. We propose a two-phase approach (TPA) integrating statistical and data mining methods. The first phase is conducted by a statistical method (MCFA: multi-group confirmatory factor analysis) to test the difference between national clustering factors. The second phase is conducted by a data mining method (a twolevel SOM) to develop the actual clusters within each nation. A two-level SOM is useful to effectively reduce the complexity of the reconstruction task and noise. Especially, our research tested the model with Korean and Japanese online game users because they are the frontier of global online game industries.

Keywords

Self-organizational map; Cross-national analysis; Online game; Market segmentation

Filed under Miscellaneous, Other Publications

A Structural Equation Modeling of the Internet Acceptance in Korea

November 4, 2010

Kim, B., Park, S., Lee, K., A Structural Equation Modeling of the Internet Acceptance in Korea, Electronic Commerce: Research and Applications, 6:425–432, 2007. SSCI. ISSN 1567-4223. pdf

Abstract

The objective of this study is to develop and test an integrated conceptual model of the Internet acceptance. Based on the two dominant theoretical paradigms – the theory of reasoned action (TRA) and the technology acceptance model (TAM) – we propose a model of the Internet acceptance to investigate the relationship between external variables such as individual differences, task characteristics and management support, and individual acceptance of the Internet. The model is tested using data gathered from 374 end users of the Internet in Korean firms and data analysis is conducted using a structural equation modeling with LISREL. Significant relationships are found between experience and usefulness, between experience and ease of use, and between ease of use and usefulness. Organizational support is found to influence usefulness, ease of use and subjective norm. We also observe that actual usage is not influenced by subjective norm, but significantly influenced by experience, usefulness and ease of use. This result implies that individual acceptance of the Internet is significantly related to external factors such as experience, task characteristics and organizational characteristics rather than beliefs

Keywords

Internet acceptance, Technology acceptance model, Self-efficacy, Experience, Task characteristic, Organizational support

Filed under Miscellaneous, Other Publications

Rethinking Preferential Attachment Scheme in the dynamic network: Degree centrality or closeness centrality

November 4, 2010

Ko, K., Lee, K., Park, C., Rethinking Preferential Attachment Scheme in the dynamic network: Degree centrality or closeness centrality?, Connections 27(3):53-59, 2007. ISSN 0226-1776. pdf

Abstract

Construction of realistic dynamic complex network has become increasingly important. One of widely known approaches, Barabasi and Albert’s “scale-free” network (BA network), has been generated under the assumption that new actors make ties with high degree actors. Unfortunately, degree, as a preferential attachment scheme, is limited to a local property of network structure, which social network theory has pointed out for a long time. In order to complement this shortcoming of degree preferential attachment, this paper not only introduces closeness preferential attachment, but also compares the relationships between the degree and closeness centrality in three different types of networks: random network, degree preferential attachment network, and closeness preferential attachment network. We show that a high degree is not a necessary condition for an actor to have high closeness. Degree preferential attachment network and sparse random network have relatively small correlation between degree and closeness centrality. Also, the simulation of closeness preferential attachment network suggests that individuals’ efforts to increase their own closeness will lead to inefficiency in the whole network.

Filed under Network Science, Other Publications

Criteria of Good Project Network Generator and its Fulfillment using a Dynamic CBR Approach

November 4, 2010

Kim, H. Lee, K., Criteria of Good Project Network Generator and its Fulfillment using a Dynamic CBR Approach, Lecture Notes in Computer Science 3155:630-644, September, 2004. – SCIE, ISSN:0302-9743. pdf

Abstract

Most project-based industries such as construction, shipbuilding, and software development etc. should generate and manage project network for successful project planning. We suggest a set of criteria of good project network generator such as network generation efficiency, quality of network, and economics of system development. For the efficiency of the planning, the first criterion, we decided to take a CBR approach. However, using only previous cases is insufficient to generate a proper network for a new project. By embedding rules and constraints in the case-based system, we could improve the quality of the project network: the second criterion. The integration of CBR approach and the knowledge-based approach makes feasible the development of the project network generator and improves the quality of the network by mutual enhancement through crosschecking the knowledge and cases in the development and maintenance stages. For some complex project network planning, a single-case assumed project network generation methodology is refined into Dynamic Leveled Multiple Case approach. The methodology contributes again the efficiency and effectiveness of project network generation and reduces the efforts of the system development.

Filed under Expert Systems, Other Publications

DAS: Intelligent Scheduling Systems for Shipbuilding

November 4, 2010

Lee, J. K., Lee, K. J., Hong, J. S., Kim, W. J., Kim, E. Y., Choi, S. Y., Kim, H. D., Yang, O. R., Choi, H. R., “DAS: Intelligent Scheduling Systems for Shipbuilding”, AI Magazine, vol. 16, no. 2, pp. 78-94, Winter, 1995.pdf

Abstract

Daewoo Shipbuilding Company, one of the largest shipbuilders in the world, has experienced a great deal of trouble with the planning and scheduling of its production process. To solve the problems, from 1991 to 1993, Korea Advanced Institute of Science and Technology (KAIST) and Daewoo jointly conducted the Daewoo Shipbuilding Scheduling (das) Project. To integrate the scheduling expert systems for shipbuilding, we used a hierarchical scheduling architecture. To automate the dynamic spatial layout of objects in various areas of the shipyard, we developed spatial scheduling expert systems. For reliable estimation of person-hour requirements, we implemented the neural network–based person-hour estimator. In addition, we developed the paneledblock assembly shop scheduler and the longrange production planner. For this large-scale project, we devised a phased development strategy consisting of three phases: (1) vision revelation, (2) data-dependent realization, and (3) prospective enhancement. The DAS systems were successfully launched in January 1994 and are actively being used as indispensable systems in the shipyard, resulting in significant improvement in productivity and visible and positive effects in many areas.

Filed under Expert Systems, Other Publications

A Spatial Scheduling System and its Application to Shipbuilding: DAS-CURVE

November 4, 2010

Lee, K. J., J. K. Lee, S. Y. Choi, “A Spatial Scheduling System and its Application to Shipbuilding: DAS-CURVE”, Expert Systems with Applications, vol. 10, no.3/4 , pp. 311-324, 1996.pdf

Abstract

Spatial scheduling considers not only traditional scheduling constraints like resource capacity and due dates, but also dynamic spatial layout of the objects. Automation of spatial scheduling is particularly important when the spatial resources are critical bottleneck resources, as is the case in the shipbuilding industry. To develop a spatial scheduling expert system for shipbuilding, a methodology for spatial layout of polygonal objects within rectangular plates is first developed. This study is then extended to the methodology for spatial scheduling, including the time dimension. The methodology is applied to the scheduling of Daewoo shipbuilding to build a system DAS-CURVE. DAS-CURVE is successfully operational and its experimental performance is remarkable.

Filed under Expert Systems, Other Publications

Developing Scheduling Systems for Daewoo Shipbuilding: DAS Project

November 4, 2010

Lee, J. K., Lee, K. J., Park, H. K., Hong, J. S., Lee, J. S., “Developing Scheduling Systems for Daewoo Shipbuilding: DAS Project”, European Journal of Operational Research, vol. 97, no.2, pp.380-395, 1997.pdf

Abstract

Daewoo Shipbuilding Company, one of the largest shipbuilders in the world, had difficulties with planning and scheduling its production process. To solve the problems, Korea Advanced Institute of Science and Technology (KAIST) and Daewoo have been jointly performing the DAS (DAewoo Shipbuilding Scheduling) Project for three years from 1991 to 1993. To develop the integrated scheduling systems, several technological breakthroughs were necessary such as hierarchical architecture between systems, constraint directed graph search, spatial scheduling, dynamic assembly line scheduling, and neural network based man-hours estimation. Besides these technological research issues, we adopted the phased development strategy, which consists of three phases of vision revelation, data dependent realization, and prospective enhancement. The DAS systems were successfully launched in January 1994 and are being actively used as indispensable systems in the shipyard resulting in a significant improvement in productivity and reengineering of the scheduling process.

Keywords

Scheduling, Manufacturing Industries, Artificial Intelligence, Shipbuilding.

Filed under Expert Systems, Other Publications

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