• The Korean Journal of Nuclear Medicine Technology
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• v.16 no.1
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• pp.17-26
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• 2012

Purpose: This study mainly focuses on the patients treated with chemically stable radiopharmaceutical product $^{99m}Tc$-HMPAO (d,l-hexamethylpropylene amine oxime) which yielded reduced image quality due to a decreased brain extraction rate. $^{99m}Tc$-HMPAO will be examined further to determine whether this product may be accounted as a factor for this cause. Material and Methods: From January 2010 until December 2010, out of 272 patients who were all subjected to $^{99m}Tc$-HMPAO brain blood flow SPECT scans resulting from Cerebral Infarction; 23 patients(ages $55.3{\pm}9$, 21 males, 3 females) with decreased tissue extraction rate were examined in detail. The radiopharmaceutical product $^{99m}Tc$-HMPAO was used on patients with normal brain tissue exchange rate as well as those with reduced rate in order to prove its' chemical stability. The patients' age, sex, blood pressure, existence of diabetes, drug use, current health status, known side effects from CT/MRI, examination of the patients' past SPECT before/after images were accounted to determine the factors and correlations affecting the rate of blood tissue extractions. Result: After multiple linear regression analysis, there were no unusual correlations between the 6 factors excluding sex, and before/after examination images. Male subjects showed reduced brain tissue extraction rate than the females ($p$ > 0.05) 91.3% male, 8.7% female. Wilcoxon Matched-Pairs Signed-Ranks Test was used on the before/after images which yielded a value of 0.06, which did not indicate a significant amount of difference on the 2 tests ($p$ > 0.05). As a result, the before/after images indicated similar brain tissue extraction rates, and there were variations depending on the individual patient. Conclusion: The effects of the chemically stable radiopharmaceutical product $^{99m}Tc$-HMPAO depended on the patient's personal characteristics and status, therefore was considered to be a factor in reducing brain tissue extraction rate. The related articles of $^{99m}Tc$-HMPAO cerebral blood flow SPECT speculates a cerebrovascular disease and factors resulting from portal veins, and it was not possible to pin point the exact cause of decreasing brain tissue extraction rate. However, the $^{99m}Tc$-HMPAO cerebral blood flow SPECT scan proved to be extremely useful in tracking and inspecting brain diseases, as well as offering accurate results from patients suffering from reduced brain tissue extraction rates.

• Journal of agricultural medicine and community health
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• v.35 no.3
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• pp.260-273
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• 2010

Objectives: The purpose of this study was to investigate the perceptions of married Korean women regarding marriage and childbirth, and their awareness of childbirth-related issues such as low birth rates, sex preferences and sex imbalances in Korea. Methods: A total of 453 married women aged 20 or older were randomly selected from four urban districts and five rural districts out of 25 districts in Gyeongju, a consolidated city located in Gyeongsangbuk-do Province, South Korea. The survey was conducted from December 2005 to February 2006. A total of 392 out of 453 questionnaires(86.5% response rate) were collected, and 44 incomplete questionnaires were excluded, leaving 348 completed questionnaires to be used for data analysis. Age was divided into three groups as below 49, 50-69, 70 or older. Results: Women's perceptions of marriage were associated with age(p<0.01). Perceptions about childbirth were also significantly related to age(p<0.01), type of residential area (p<0.01) and education level(p<0.05). Sex preferences were significantly related to age(p<0.05) and occupation(p<0.01). Of the respondents aged 49 or younger, 34.8% indicated that the ideal number of children is two, while 25.5% of respondents aged 50 to 69 and 15.3% of respondents aged 70 and 33.7% of respondents aged 70 or older considered four children to be the ideal number. Perceptions of sex imbalance were significantly related to socioeconomic status(p<0.01) and occupation(p<0.01). The largest number of respondents cited "economic burden" as the main reason for low birth rates. Multiple logistic regressions were performed for all three age groups using male sex preference as the dependent variable under the assumption that respondents can have only a single child. Socioeconomic status (p<0.01) and residential area (p<0.05) were significant variables for those aged 49 or below. Education level(p<0.05) and residential area (p<0.01) were statistically significant variables on preferring son in case of having only one child for respondents aged 50 to 69. We did not detect any significant independent variables in respondents who were 70 or older. Conclusions: Our results highlight the necessity of developing policies and public education programs to explain the consequences of low birth rates and sex imbalances in Korea. As increasing numbers of women work outside the home, it is important for the government and employers to provide social and working environments where women do not consider marriage and childbirth to be obstacles to social and business activities.

• Radiation Oncology Journal
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• v.27 no.1
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• pp.15-22
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• 2009

Purpose: This study was designed to evaluate the effects on bone mineral density (BMD) and related factors according to the distance from the radiation field at different sites. This study was conducted on patients with uterine cervical cancer who received pelvic radiotherapy. Materials and Methods: We selected 96 patients with cervical cancer who underwent determination of BMD from November 2002 to December 2006 after pelvic radiotherapy at Kosin University Gospel Hospital. The T-score and Z-score for the first lumbar spine (L1), fourth lumbar spine (L4) and femur neck (F) were analyzed to determine the difference in BMD among the sites by the use of ANOVA and the post-hoc test. The study subjects were evaluated for age, body weight, body mass index (BMI), post-radiotherapy follow-up duration, intracavitary radiotherapy (ICR) and hormonal replacement therapy (HRT). Association between the characteristics of the study subjects and T-score for each site was evaluated by the use of Pearson's correlation and multiple regression analysis. Results: The average T-score for all ages was -1.94 for the L1, -0.42 for the L4 and -0.53 for the F. The average Z-score for all ages was -1.11 for the L1, -0.40 for the L4 and -0.48 for the F. The T-score and Z-score for the L4 and F were significantly different from the scores for the L1 (p<0.05). There was no significant difference between the L4 and F. Results for patients younger than 60 years were the same as for all ages. Age and ICR were negatively correlated and body weight and HRT were positively correlated with the T-score for all sites (p<0.05). BMI was positively correlated with the T-score for the L4 and F (p<0.05). Based on the use of multiple regression analysis, age was negatively associated with the T-score for the L1 and F and was positively correlated for the L4 (p<0.05). Body weight was positively associated with the T-score for all sites (p<0.05). ICR was negatively associated with the T-score for the L1 (p<0.05). HRT was positively associated with the T-score for the L4 and F (p<0.05). Conclusion: The T-score and Z-score for the L4 and F were significantly higher than the scores for the L1, a finding in contrast to some previous studies on normal women. It was thought that radiation could partly influence BMD because of a higher T-score and Z-score for sites around the radiotherapy field. We suggest that a further long-term study is necessary to determine the clinical significance of these findings, which will influence the diagnosis of osteoporosis based on BMD in patients with cervical cancer who have received radiotherapy.

• Journal of the Korean Society of Food Science and Nutrition
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• v.41 no.9
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• pp.1265-1273
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• 2012

The purpose of this study was to investigate the BMI, intake of snacks, and perceptions and use of food and nutrition labels by middle school students (144 boys and 189 girls) in Chuncheon area. The average height and weight of boys were $171.0{\pm}6.4$ cm and $61.0{\pm}11.4$ kg, respectively, whereas those of girls were $160.0{\pm}4.8$ cm and $50.8{\pm}6.6$ kg, respectively. Average body mass index (BMI) of boys and girls were $20.8{\pm}3.3$ and $19.8{\pm}2.4$, respectively (p<0.01). Dietary intake attitude score of girls ($34.39{\pm}5.66$) was higher than that of boys ($33.92{\pm}5.40$) (p<0.05). Subjects bought and ate snacks 1 to 3 times per week (40.2%) by themselves, and most consumed snacks were cookies (23.1%), instant noodles (16.2%), ice cream (13.2%), and candy and chocolates (13.2%). The most important factor in purchasing of snacks was 'taste' ($4.49{\pm}0.67$). When subjects bought processed foods, the rates of reading food labels was 86.6%. The most important factor of the food labels was 'expiration date' (42.9%). The degree of reading food labels on processed foods by girls ($22.70{\pm}5.72$) was higher than that of boys ($20.96{\pm}5.35$) (p<0.01). Of the 13.2% of subjects that did not read food labels, the reason why was that they were not interested (50.0%). Of the 78.4% of subjects that read nutrition labels, the most important component of the nutrition labels was 'calories' (75.9%). The main reason for reading nutrition labels was 'to control weight' (45.6%). In general, use of food labels correlated positively with dietary intake attitude score (p<0.05) and use of nutrition labels (p<0.01). Using multiple regression analysis, we found that 'usefulness of dietary life' was the most significant variable that affects the importance of food and nutrition labels. Therefore, development of an educational program on food and nutrition labels for adolescents will be effective in improving dietary life.

• Journal of Preventive Medicine and Public Health
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• v.24 no.3 s.35
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• pp.363-372
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• 1991

We used the health screening data of some rural and urban residents to examine the cross-sectional association between leukocyte count and hypertension. The 206 male and 203 female rural residents were selected by multi-stage cluster sampling method in Kyungsan-Kun area of Kyungbuk province in 1985 and 600 urban residents were selected by the same sampling method as the rural residents in Daegu city of the same province in 1986 compatible with age-sex distribution of Daegu city of 1985 census, but of whom 384 actually responded. The rest of 600 were replaced by age and sex with those who were members of the medical insurance plan visiting the health management department of the university hospital to get the biannual preventive medical checkups. Excluded in the analysis were those having hypertensive history, diseases and extreme outlying values of the screening tests, leaving 373 rural and 571 urban residents. Leukocyte count was measured with ELT-8 Laser shadow method and the unit $cells/mm^3$, Blood pressures were determined with an aneroid sphygmomanometer with pre-standardized method and hypertensives were defined as those showing systolic blood pressure more than 140mmHg and/or diastolic blood pressure more than 90mmHg. Total residents pooled (N=944) showed a significant difference between hypertensives and normotensives ($6965.93{\pm}1997.01\;vs\;6490.61{\pm}1941.32,\;P=0.00$) and in rural residents was noted the similar significant difference (P=0.03). None of significant differences were noted in any stratum stratified by residency and sex. Compared to the lowest quintile of WBC, 2/5 quintile showed odds ratio 0.99 (95% Confidence interval, Ci 0.62-1.59), 3/5 quintile 1.41 (95% CI 0.90-2.21), 4/5 quintile 1.76 (95% CI. 1.14-2.72), and highest quintile 1.80 (1.15-2.82) in the total residents. Likelihood ratio test for linear trend for it indicated a significant trend ($X^2_{trend}=5.53,\;df=1,\;P<0.05$). There were no other significant odds ratios compared to the lowest quintile of WBC in strata stratified by residency and sex. The odds ratios in total residents which had showed significant odds ratios became nonsignificant and of reduced magnitude after controlling age, frequency of smoking and drinking with multiple logistic. regression. In each stratum, it changed magnitudes of odds ratios slightly and unstably. None of the trend tests showed any significant trend. These results suggest that the Friedman et al's finding of association between leukocyte count and hypertension may be due to an statistical type I error resulting from the data dredging in an exploratory study, in which more than 800 variables were screened as possible predictors of hypertension.

• Journal of Preventive Medicine and Public Health
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• v.25 no.2 s.38
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• pp.127-140
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• 1992

This study was done to identify the association between serum copper and zinc levels and the cirrhosis and hepatocellular carcinoma(HCC), and to evaluate its diagnostic value on liver diseases. Sixty-three healthy persons, 60 patients with cirrhosis and 33 patients with hepatocellular carcinoma were rendomly selected and investigated for their general characteristics from October 1990 to August 1991. For analysis of the biochemical markers in liver function test and the serum copper and zinc levels, their fasting venous blood were sampled at 9:00 to 11:00 in the morning and centrifuged to separate the serum within one hour. All the samples were immediately analysed for biochemical markers and stored at $-20^{\circ}C$ in polypropylene tubes further copper and zinc analysis. Mean of serum coppper levels was $91.97{\pm}4.76{\mu}g/dl$ in control, $106.21{\pm}2.73{\mu}g/dl$ in cirrhosis and $127.05{\pm}0.77{\mu}g/dl$ in HCC. The value of HCC was statistically significantly higher than that of the control and cirrhosis(p<0.05). Serum zinc levels were $110.82{\pm}7.24{\mu}g/dl$ in control, $68.10{\pm}5.43{\mu}g/dl$ in cirrhosis and $63.78{\pm}2.20{\mu}g/dl$ in HCC. The values of cirrhosis and HCC were statistically significantly lower than that of control(p<0.05). The Cu/Zn ratio was statiatically significantly different among three groups(p<0.05). Test total protein, albumin, ALP and total bilirubin of biochemical markers of liver function were statistically significantly different among three groups(p<0.05). Differences between cirrhosis and HCC for ALT and AST, and between the control and HCC for direct bilirubin were not statistically significant. Biochemical markers statistically significantly correlated with serum copper and zinc levels and Cu/Zn ratio(p<0.05), were variable in three groups. In multiple logistic regression, odds ratio of serum copper level and Cu/Zn ratio had no statistical significance on the cirrhosis and the HCC, but that of serum sinc was statistically significant as 0.951 and 0.952(p<0.05). Serum copper and zinc levels and Cu/Zn ratio were not statistically significantly different between the cirrhosis and HCC. H\Albumin, ALP, zinc, total bilirubin and age among all variables were selected as main variables for three-group discriminant analysis. Percentage of 'grouped' cases correctly classified by these five variables was 98.4 for control, 73.4 for cirrhosis, 75.7 for HCC and 84.0 for all subjects. This study suggests that zinc level is considered to play a role as diagnostic marker on the hepatic disorders and be more useful than serum copper level and Cu/Zn ratio in diagnosis of the liver diseases.

• Korean Journal of Agricultural Science
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• v.16 no.2
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• pp.212-224
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• 1989

This paper reports results of an investigation to determine properties of superplasticizered fly ash concrete. The mixture proportions of fly ash were 0, 10, 20 and 30%, by weight of cement, and superplasticizer was added as a percentage of fly ash, 0, 0.6, 12 and 1.8%. To investigate the effective use of the superplasticized fly ash concrete, the basic data were analyzed. The results obtained were summarized as follows : 1. The unit water content was decreased by 1%, 6% and increased by 2% to the ratio of addition of fly ash 10%, 20%, 30%, respectively, but in case of the superplasticized fly ash concrete, it was decreased by 3~16%, 4~14% and 10~17%, at 0.6, 12, and 1.8% dosage of superplasticizer, respectively. 2. In the properties of the fresh fly ash concrete, the slump loss was reduced with the ratio of replacement of fly ash increased, and with times went by. When using superplasticizer in fly ash substituting concrete, the fludity in the concrete was not decreased. 3. The compressive strength of fly ash concrete at early ages was lower than that of ordinary concrete. At the later age of 28 days, the compressive strength with 20% addition of fly ash was increased than that of ordinary concrete. In cased of 10%, 30% addition of fly ash, the compressive strength were reduced. From this, it was proved that the optimum amount of fly ash appears to be about 20%. The compressive strength at all ages of superplasticized fly ash concrete was significantly higher than that of fly ash concrete, with increasing fly ash content. 4. In case of the tensile strength, the effects of the increasing strength with the ages were similar to those of the compressive strtength, and at the later ages was seen a decreasing tendency of strengths. 5. The correlation between compressive and tensile strength of superplasticized fly ash concrete was highly significant. The multiple regression equations of compressive and tensile strength were obtained on a function of the mixture proportion of fly ash and the addition of superplasticizer. The relation between compressive and tensile strength is higher than for ordinary concrete. The strength ratio is 7~11, and it is higher than that of ordinary concrete, 8~10. 6. Bulk density was decreased by 1~3% compared with ordinary concrete with the mixture proportion of fly ash increased, 10~30%, and decreased by 1~2% with the superplasticizer added 0.6~1.8%.

• Journal of Sericultural and Entomological Science
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• v.10
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• pp.35-40
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• 1969

Various formulae for estimation of spring leaf production in mulberry trees were calculated and obtained. Four varieties of mulberry trees were used as the materials, and four characters, namely branch length (X$_1$), node number (X$_2$), branch diameter (X$_3$) and branch number per stock (X$_4$) were studied. The formulae to estimate the leaf yield of spring mulberry trees are as follows: 1. $Y_1$v$_1$= -26.8939＋50.3950X$_1$＋1.1403X$_2$ $Y_1$v$_2$= -372.1091＋116.6371X$_1$＋0.1984X$_2$ $Y_1$v$_3$= 149.8203＋90.5125X$_1$-0.9775X$_2$ $Y_1$v$_4$= 108, 1496＋59.4533X$_1$＋1.4965X$_2$ Where $Y_1$v$_1$, $Y_1$v$_2$, $Y_1$v$_3$, $Y_1$v$_4$, are showed the estimated yield of the each variety, namely Gaeryang Seuban, Ilchirye, Nosang, and Suwon Sang No. 4, respectively. X$_1$ and X$_2$ denote the measured values of branch length and node number, respectively. 2. $Y_{7}$v$_1$= -54.4411＋32.9869c1.1127X$_2$＋21.7600X$_3$ $Y_{7}$v$_2$= -494.1480-1.8756X$_1$＋0.9788X$_2$＋110.0039X$_3$ $Y_{7}$v$_3$= 143.2836＋29.1779X$_1$＋0.1644X$_2$＋48.4135X$_3$ $Y_{7}$v$_4$= 1243.2549＋1.9454X$_1$＋2.7118X$_2$-75.6669X$_3$ Where $Y_{7}$v$_1$, $Y_{7}$v$_2$, $Y_{7}$v$_3$, $Y_{7}$v$_4$, are the estimated yield of the each variety, namely Gaeryang-Seuban, Ilchirye, Nosang, Suwon Sang No 4, respectively. X$_1$, X$_2$, X$_3$ denote the measured values of each character, branch length, node number, branch diameter and branch number per stock, respectively. 3. $Y_{11}$v$_1$=233.4780＋74.3713X$_1$＋1.2912X$_2$＋39.0420X$_3$-148.9300X$_4$ $Y_{11}$v$_2$=-317.0150＋15.l524X$_1$＋1.0861X$_2$＋156.7973X$_3$-148.3742X$_4$ $Y_{11}$v$_3$=178.7011＋29.8664X$_1$-0.2562X$_2$＋102.4632X$_3$-83.2693X$_4$ $Y_{11}$v$_4$= 264.0062＋47.7742X$_1$＋2.6996X$_2$＋92.8882X$_3$-192.3464X$_4$ Where $Y_{11}$v$_1$, $Y_{11}$v$_2$, $Y_{11}$v$_3$, $Y_{11}$v$_4$, are the estimated yield values of four varieties, and X$_1$, X$_2$, X$_3$, X$_4$, denote the measured values of four characters, namely branch length, node number, branch diameter and branch number per stock, respectively. The estimation method of mulberry spring leaf yield by measurement of some characters, in autumn the year before, could be the better method to determine the leaf yield of mulberry trees without destroying the leaves and without weighting the leaves of mulberry trees than the other methods.

• Journal of Intelligence and Information Systems
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• v.23 no.4
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• pp.147-168
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• 2017

There have been many studies on accurate stock market forecasting in academia for a long time, and now there are also various forecasting models using various techniques. Recently, many attempts have been made to predict the stock index using various machine learning methods including Deep Learning. Although the fundamental analysis and the technical analysis method are used for the analysis of the traditional stock investment transaction, the technical analysis method is more useful for the application of the short-term transaction prediction or statistical and mathematical techniques. Most of the studies that have been conducted using these technical indicators have studied the model of predicting stock prices by binary classification - rising or falling - of stock market fluctuations in the future market (usually next trading day). However, it is also true that this binary classification has many unfavorable aspects in predicting trends, identifying trading signals, or signaling portfolio rebalancing. In this study, we try to predict the stock index by expanding the stock index trend (upward trend, boxed, downward trend) to the multiple classification system in the existing binary index method. In order to solve this multi-classification problem, a technique such as Multinomial Logistic Regression Analysis (MLOGIT), Multiple Discriminant Analysis (MDA) or Artificial Neural Networks (ANN) we propose an optimization model using Genetic Algorithm as a wrapper for improving the performance of this model using Multi-classification Support Vector Machines (MSVM), which has proved to be superior in prediction performance. In particular, the proposed model named GA-MSVM is designed to maximize model performance by optimizing not only the kernel function parameters of MSVM, but also the optimal selection of input variables (feature selection) as well as instance selection. In order to verify the performance of the proposed model, we applied the proposed method to the real data. The results show that the proposed method is more effective than the conventional multivariate SVM, which has been known to show the best prediction performance up to now, as well as existing artificial intelligence / data mining techniques such as MDA, MLOGIT, CBR, and it is confirmed that the prediction performance is better than this. Especially, it has been confirmed that the 'instance selection' plays a very important role in predicting the stock index trend, and it is confirmed that the improvement effect of the model is more important than other factors. To verify the usefulness of GA-MSVM, we applied it to Korea's real KOSPI200 stock index trend forecast. Our research is primarily aimed at predicting trend segments to capture signal acquisition or short-term trend transition points. The experimental data set includes technical indicators such as the price and volatility index (2004 ~ 2017) and macroeconomic data (interest rate, exchange rate, S&P 500, etc.) of KOSPI200 stock index in Korea. Using a variety of statistical methods including one-way ANOVA and stepwise MDA, 15 indicators were selected as candidate independent variables. The dependent variable, trend classification, was classified into three states: 1 (upward trend), 0 (boxed), and -1 (downward trend). 70% of the total data for each class was used for training and the remaining 30% was used for verifying. To verify the performance of the proposed model, several comparative model experiments such as MDA, MLOGIT, CBR, ANN and MSVM were conducted. MSVM has adopted the One-Against-One (OAO) approach, which is known as the most accurate approach among the various MSVM approaches. Although there are some limitations, the final experimental results demonstrate that the proposed model, GA-MSVM, performs at a significantly higher level than all comparative models.

• Information Systems Review
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• v.16 no.3
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• pp.161-177
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• 2014

Corporate credit rating assessment consists of complicated processes in which various factors describing a company are taken into consideration. Such assessment is known to be very expensive since domain experts should be employed to assess the ratings. As a result, the data-driven corporate credit rating prediction using statistical and artificial intelligence (AI) techniques has received considerable attention from researchers and practitioners. In particular, statistical methods such as multiple discriminant analysis (MDA) and multinomial logistic regression analysis (MLOGIT), and AI methods including case-based reasoning (CBR), artificial neural network (ANN), and multiclass support vector machine (MSVM) have been applied to corporate credit rating.2) Among them, MSVM has recently become popular because of its robustness and high prediction accuracy. In this study, we propose a novel optimized MSVM model, and appy it to corporate credit rating prediction in order to enhance the accuracy. Our model, named 'GAMSVM (Genetic Algorithm-optimized Multiclass Support Vector Machine),' is designed to simultaneously optimize the kernel parameters and the feature subset selection. Prior studies like Lorena and de Carvalho (2008), and Chatterjee (2013) show that proper kernel parameters may improve the performance of MSVMs. Also, the results from the studies such as Shieh and Yang (2008) and Chatterjee (2013) imply that appropriate feature selection may lead to higher prediction accuracy. Based on these prior studies, we propose to apply GAMSVM to corporate credit rating prediction. As a tool for optimizing the kernel parameters and the feature subset selection, we suggest genetic algorithm (GA). GA is known as an efficient and effective search method that attempts to simulate the biological evolution phenomenon. By applying genetic operations such as selection, crossover, and mutation, it is designed to gradually improve the search results. Especially, mutation operator prevents GA from falling into the local optima, thus we can find the globally optimal or near-optimal solution using it. GA has popularly been applied to search optimal parameters or feature subset selections of AI techniques including MSVM. With these reasons, we also adopt GA as an optimization tool. To empirically validate the usefulness of GAMSVM, we applied it to a real-world case of credit rating in Korea. Our application is in bond rating, which is the most frequently studied area of credit rating for specific debt issues or other financial obligations. The experimental dataset was collected from a large credit rating company in South Korea. It contained 39 financial ratios of 1,295 companies in the manufacturing industry, and their credit ratings. Using various statistical methods including the one-way ANOVA and the stepwise MDA, we selected 14 financial ratios as the candidate independent variables. The dependent variable, i.e. credit rating, was labeled as four classes: 1(A1); 2(A2); 3(A3); 4(B and C). 80 percent of total data for each class was used for training, and remaining 20 percent was used for validation. And, to overcome small sample size, we applied five-fold cross validation to our dataset. In order to examine the competitiveness of the proposed model, we also experimented several comparative models including MDA, MLOGIT, CBR, ANN and MSVM. In case of MSVM, we adopted One-Against-One (OAO) and DAGSVM (Directed Acyclic Graph SVM) approaches because they are known to be the most accurate approaches among various MSVM approaches. GAMSVM was implemented using LIBSVM-an open-source software, and Evolver 5.5-a commercial software enables GA. Other comparative models were experimented using various statistical and AI packages such as SPSS for Windows, Neuroshell, and Microsoft Excel VBA (Visual Basic for Applications). Experimental results showed that the proposed model-GAMSVM-outperformed all the competitive models. In addition, the model was found to use less independent variables, but to show higher accuracy. In our experiments, five variables such as X7 (total debt), X9 (sales per employee), X13 (years after founded), X15 (accumulated earning to total asset), and X39 (the index related to the cash flows from operating activity) were found to be the most important factors in predicting the corporate credit ratings. However, the values of the finally selected kernel parameters were found to be almost same among the data subsets. To examine whether the predictive performance of GAMSVM was significantly greater than those of other models, we used the McNemar test. As a result, we found that GAMSVM was better than MDA, MLOGIT, CBR, and ANN at the 1% significance level, and better than OAO and DAGSVM at the 5% significance level.