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Bankruptcy Type Prediction Using A Hybrid Artificial Neural Networks Model (하이브리드 인공신경망 모형을 이용한 부도 유형 예측)

  • Jo, Nam-ok;Kim, Hyun-jung;Shin, Kyung-shik
    • Journal of Intelligence and Information Systems
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    • v.21 no.3
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    • pp.79-99
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    • 2015
  • The prediction of bankruptcy has been extensively studied in the accounting and finance field. It can have an important impact on lending decisions and the profitability of financial institutions in terms of risk management. Many researchers have focused on constructing a more robust bankruptcy prediction model. Early studies primarily used statistical techniques such as multiple discriminant analysis (MDA) and logit analysis for bankruptcy prediction. However, many studies have demonstrated that artificial intelligence (AI) approaches, such as artificial neural networks (ANN), decision trees, case-based reasoning (CBR), and support vector machine (SVM), have been outperforming statistical techniques since 1990s for business classification problems because statistical methods have some rigid assumptions in their application. In previous studies on corporate bankruptcy, many researchers have focused on developing a bankruptcy prediction model using financial ratios. However, there are few studies that suggest the specific types of bankruptcy. Previous bankruptcy prediction models have generally been interested in predicting whether or not firms will become bankrupt. Most of the studies on bankruptcy types have focused on reviewing the previous literature or performing a case study. Thus, this study develops a model using data mining techniques for predicting the specific types of bankruptcy as well as the occurrence of bankruptcy in Korean small- and medium-sized construction firms in terms of profitability, stability, and activity index. Thus, firms will be able to prevent it from occurring in advance. We propose a hybrid approach using two artificial neural networks (ANNs) for the prediction of bankruptcy types. The first is a back-propagation neural network (BPN) model using supervised learning for bankruptcy prediction and the second is a self-organizing map (SOM) model using unsupervised learning to classify bankruptcy data into several types. Based on the constructed model, we predict the bankruptcy of companies by applying the BPN model to a validation set that was not utilized in the development of the model. This allows for identifying the specific types of bankruptcy by using bankruptcy data predicted by the BPN model. We calculated the average of selected input variables through statistical test for each cluster to interpret characteristics of the derived clusters in the SOM model. Each cluster represents bankruptcy type classified through data of bankruptcy firms, and input variables indicate financial ratios in interpreting the meaning of each cluster. The experimental result shows that each of five bankruptcy types has different characteristics according to financial ratios. Type 1 (severe bankruptcy) has inferior financial statements except for EBITDA (earnings before interest, taxes, depreciation, and amortization) to sales based on the clustering results. Type 2 (lack of stability) has a low quick ratio, low stockholder's equity to total assets, and high total borrowings to total assets. Type 3 (lack of activity) has a slightly low total asset turnover and fixed asset turnover. Type 4 (lack of profitability) has low retained earnings to total assets and EBITDA to sales which represent the indices of profitability. Type 5 (recoverable bankruptcy) includes firms that have a relatively good financial condition as compared to other bankruptcy types even though they are bankrupt. Based on the findings, researchers and practitioners engaged in the credit evaluation field can obtain more useful information about the types of corporate bankruptcy. In this paper, we utilized the financial ratios of firms to classify bankruptcy types. It is important to select the input variables that correctly predict bankruptcy and meaningfully classify the type of bankruptcy. In a further study, we will include non-financial factors such as size, industry, and age of the firms. Thus, we can obtain realistic clustering results for bankruptcy types by combining qualitative factors and reflecting the domain knowledge of experts.

Studies on Inheritance and Ecological Variation of the Culm Length and Its Related Characters in Short-Statured Rice Varieties (수도단간품종의 간장 및 관련형질의 유전과 생태적 변이에 관한 연구)

  • Sung-Ho Bea
    • KOREAN JOURNAL OF CROP SCIENCE
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    • v.13
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    • pp.1-40
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    • 1973
  • These studies were aimed at clarification of genetic and ecological variation in culm length, panicle length and plant height of the $\textrm{F}_2$ plants in some selected crosses made between semi-dwarf rice varieties and tall Japonica ones. One Indica semi-dwarf, Taichung Native 1, one Indica $\times$ Japonica hybrid, IE51 and one Japonica semi-dwarf, Tankanbaekmang were used as short-gene donors while two of medium maturity varieties, Jinheung and Kwanok and one late veriety, Palkweng were used as the corresponding counterpart of respective dwarf varieties in a series of crosses. Five different crosses, Kwanok $\times$ Tankanbaekmang, Palkweng $\times$ Tankanbaekmang, Jinheung $\times$ T(N)1, Kwanok $\times$ T(N)1 and Kwanok $\times$ IE51, were made among the above six varieties. The $\textrm{F}_2$ plants of these crosses together with the concerned parental varieties were grown under several different conditions including three levels of each nitrogen and planting space, three planting seasons and three locations in 1968, to investigate variation in length of culm and panicle, and plant height. On the other hand, the F$_3$ progenies which were derived from the shortest 10 percent of the plants of three $\textrm{F}_2$ populations, Kwanok $\times$ T(N)1, Jinheung $\times$ T(N) 1 and Kwanok $\times$ IE51 grown in the previous year, were compared each other on the basis of selection efficiency in culm length. The experimental results could be summarized as follows; 1. Genetic behavior A. It was revealed that Tankanbaekmang, one of Japonica dwarf has a simple recessive gene responsible for short culm expression, showing a typical segregation ratio of three tall to one short culm plants in $\textrm{F}_2$ generation of the crosses either with Kwanok or Palkweng. B. In the both combinations, segregation pattern of the panicle length was exactly same as that of culm length. It seems that the same gene controls both culm length and panicle length. C. No difference between segregation of culm length and plant height in the above crosses was observed. D. T(N)1, one of Indica semi-dwarf did not show such a simple genetic behavior as detected from the crosses with Tankanbaekmang in segregation of culm length but formed a continuous and normal distribution curve. Therefore, some nonallelic genic actions might be involved in expression of culm length of the counterpart varieties of T(N)1. In particular, a transgressive segregation appeared toward the direction of longer culm length in case of Jinheung $\times$ T(N)1. The genetic behavior of panicle length and plant height generally coincided with that of culm length in all the cases. E. IE51 demonstrated exactly the same genetic behavior as that of T(N)1 when this variety was crossed with Kwanok. It was clearly clarified that the simple recessive gene controlling dwarfism from T(N)1 was well incorporated into this variety. 2. Ecological variation A. In general, there was a decreasing tendency in culm length and plant height of rice plant as seeding delayed while it was not so noticeable in panicle length. The decreasing magnitude varied from variety to variety and from cross to cross. Genetic behavior of the culm length and related characters of these materials was not disturbed by the variation of seeding season, nitrogen level, planting space and experimental location. E. The elongation mode of the upper three internodes was very similar to the segregation mode of culm length, panicle length and plant height in $\textrm{F}_2$ populations of . all the crosses investigated in this study. Accordingly, this result confirmed that the roles of the upper three internodes are very important in manifesting plant stature in rice. C. The effect of nitrogen on culm length and the related other two characters seemed to be meager. However, it was true to show an increasing tendency of those characters as nitrogen level got increased from 4 kg to 12kg per l0a, with different magnitude depending upon variety or cross. D. Also, the effect of planting space on culm length, panicle length and plant height was relatively small in all the cases. Those characters varied again depending upon variety or cross. However, a general increasing tendency was detected in manifestation of those traits under denser planting space condition. E. All the parental varieties produced shorter culm, panicle and plant height when they were grown at the lower latitude locations. It might be attributed to the fact that their reproductive growth accelerated with increased temperature prevailing at the lower latitude locations such as Iri and Mi1yang. On the countrary, $\textrm{F}_2$ population reacted differently to the different locations from the parental varieties. All the $\textrm{F}_2$ plants produced the longest culm, panicle and plant at Milyang. 3. Selection efficiency A. The heritability of culm length in Kwanok $\times$ T(N)1, Kwanok $\times$ IE51 and Jinheung$\times$T(N)1 was 92 percent, 74 percent and 55 percent, respectively. B. The actual genetic advance for culm length obtained from the progeny lines of the selected plants(10 precent) from the $\textrm{F}_2$ generation, was comparable to the expected advance calculated from the original $\textrm{F}_2$ populations. As compared with the $\textrm{F}_2$ population, the $\textrm{F}_3$ plants of Kwanok $\times$ T(N)l shortened on the average by 20.8cm, those of Kwanok $\times$ IE51 did 8.7cm and those of Jinheung$\times$T(N)1 20.0cm, respectively. C. Panicle length of the populations was differently affected from one cross to another by the selection based upon culm length in $\textrm{F}_2$ Kwanok $\times$ T(N)1 did not show any noticeable shortening of its culm length due to the selection pressure. On the other hand, both Kwanok $\times$ IE51 and Jinheung $\times$ T(N)1 showed a considerable shortening of their panicles in case of selection for culm length. Based upon the above results, it could be concluded that the ecological variation in culm length, panicle length and plant height was relatively small and fallen within the range of genetic variation. Considering from the fact that the simple recessive gene governing short height of Tankanbaekmang always accompanied with some undesirable characters such as short panicle and extremely small grain, the short gene of T(N)1 seemed to be more useful as dwarf gene source since it did not carry short gene together with such undesirable traits.

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