• Proceedings of the Korean Operations and Management Science Society Conference
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• 2006.11a
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• pp.599-617
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• 2006

A network model and a Genetic Algorithm(GA) is proposed to solve the simultaneous estimation of the trip distribution and traffic assignment from traffic counts in the congested networks in a logit-based Stochastic User Equilibrium (SUE). The model is formulated as a problem of minimizing the non-linear objective functions with the linear constraints. In the model, the flow-conservation constraints of the network are utilized to restrict the solution space and to force the link flows meet the traffic counts. The objective of the model is to minimize the discrepancies between the link flows satisfying the constraints of flow-conservation, trip production from origin, trip attraction to destination and traffic counts at observed links and the link flows estimated through the traffic assignment using the path flow estimator in the legit-based SUE. In the proposed GA, a chromosome is defined as a vector representing a set of Origin-Destination Matrix (ODM), link flows and travel-cost coefficient. Each chromosome is evaluated from the corresponding discrepancy, and the population of the chromosome is evolved by the concurrent simplex crossover and random mutation. To maintain the feasibility of solutions, a bounded vector shipment is applied during the crossover and mutation.

• Journal of Technology Innovation
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• v.24 no.3
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• pp.139-159
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• 2016

The purpose of this study is to find out the factors which promoting career development of scientist and engineer laborforce. We made up three logit analysis models to figure out the factors affecting the career of scientist and engineer laborforce. Dependent variables were composed of job attributes in 2011, current job attribute, changing of working conditions, efforts of job seeking, university education, and personal characters. Three analysis model were composed of demand side model which including job attributes factors, supply side model which focus on employment or university education characters and total model including the demand and the supply factors. The results showed a stable career to the development of scientist and engineer laborforce's job attributes on the demand side than the supply side, such as a college education even more important. After all, the initial stable jobs and good matching policy were the most important policies to be seated in the science and engineering professions.

• Journal of Korean Society of Forest Science
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• v.96 no.4
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• pp.483-493
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• 2007

The purpose of this study is to estimate the biodiversity conservation value of Heory stock in Sun-Cheon. Expected values of residents' Willingness To Pay (WTP) was estimated using Contingent Valuation Method (CVM) which is the most popular method in estimating conservation values of biological diversities. Three different estimation methods were used in statistical estimation, and the results were different from each other. Results of statistical analysis show that the expected value of WTP in logit model is highest, 5,772 Won per month. Those of A model which conducted OLS estimation using open ended questionnaire and B-1 model which conducted OLS estimation using dichotomous choice questionnaire were 1,978 Won per month and 2,391 Won per month respectively. The average expected value of WTP from three model was 3,380. This average value was expected to reduce methodological biases.

• Journal of the Korean Institute of Landscape Architecture
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• v.23 no.1
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• pp.123-139
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• 1995

The megalopolis citizens are reevaluating the expectant value and the perception of leisure aceording to increasing the level of their incomes, The leisure of citizens is increasing in the aspect of quantity and quality of life nowadays In the site planning of leisure, the concrete understanding about people's choice of a leisure site will be the most important thing, not only for the aspect of improvement of the quality of life but also efficiencies of the land use The purposes of chi study are firstly, to find out the factors which are influenced on a choice of Outdoor leisure facilities in neighbourhood unit and to Compare the Characteristics Of Choice models between the three metropolitan areas, secondly, to predict a limitation of use areal according to the change of a needed time based on the metropolitan's standard choice model For the choice model establishment this research used Logit Model which has been used in the field of the traffic, the tourism and the economics. This research made the results which find out the influencing variables with needed times, the accessibility and the percentage of facilities. The lindtations of use areas come out the results which are predicted according to the change of needed times as a most influencing factors. The range of each preferred leisure facility is about 956 meter distant in the neighbourhood park about 644 meter distant in the pocket park about 604 meter distant in the recreation center, about 628 meter distant in the tennis court about 974 meter distant in the private hob by facility and about 528 meter distant in the library from the apartment unit The recreation center and the library are nearer facilities than the other facilities. But these facilities are surveyed to be more or less influenced by an interesting progran, a context of events and the level of useful facilities, etc.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.41 no.4
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• pp.1-8
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• 2018

Whole body fatigue detection is an important phenomenon and the factors contributing to whole body fatigue can be controlled if a mathematical model is available for its assessment. This research study aims at developing a model that categorizes whole body exertion into fatigued and non-fatigued states based on physiological and perceived variables. For this purpose, logistic regression was used to categorize the fatigued and non-fatigued subject as dichotomous variable. Normalized mean power frequency of eight muscles from 25 subjects was taken as physiological variable along with the heart rate while Borg scale ratings were taken as perceived variables. The logit function was used to develop the logistic regression model. The coefficients of all the variables were found and significance level was checked. The detection accuracy of the model for fatigued and non-fatigues subjects was 83% and 95% respectively. It was observed that the mean power frequency of anterior deltoid and the Borg scale ratings of upper and lower extremities were significant in predicting the whole body fatigued when evaluated dichotomously (p < 0.05). The findings can help in better understanding of the importance of combined physiological and perceived exertion in designing the rest breaks for workers involved in squat lifting tasks in industrial as well as health sectors.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.1
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• pp.22-39
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• 2021

This study estimated mode choice models for access travel and neighborhood travel from an SP survey in metropolitan areas where shared e-scooter services are offered. Model results show that travel time and travel cost have negative effects on mode utility. It is also revealed that people are more sensitive to travel time in access travel, whereas they are more influenced by travel cost in neighborhood travel. Looking at individual and household attributes, it has a positive effect when under 40 yerars of age, owning bikes, being a public transportation user, while it has been shown a negative effect in less than 3 million won in monthly household income and owning individual cars.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.6
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• pp.1279-1286
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• 2021

This study suggests the user's needs for a smart parking service that enables parking lot search and advance reservation service, and is a study on the user's preference selection model related to fees (reservation fee, penalty fee), etc. Two types of user preference models in the form of logit models were constructed by composing a response questionnaire for smart parking service. The first is a model for selecting a smart parking lot, which suggests a situation in which the probability of selection is higher than that of a general parking lot in the relationship between usage fee and cost. The second is a parking ticket reservation discount selection model, and the smart parking service selection probability was analyzed through the relationship model between the reservation amount and the penalty. It can be used as a design requirement that enables sophisticated and various types of smart parking service considering users' preferences.

• Journal of Distribution Science
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• v.12 no.11
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• pp.77-83
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• 2014

Purpose - The National Agricultural Cooperative Federation of Korea and National Fisheries Cooperative Federation of Korea have prosecuted both financial and retail businesses. As cooperatives are public institutions and receive government support, their sound management is required by the Financial Supervisory Service in Korea. This is mainly managed by CAEL, which is changed by CAMEL. However, NFFC's business section, managing the finance and retail businesses, is unified and evaluated; the CAEL model has an insufficient classification to evaluate the retail industry. First, there is discrimination power as regards CAEL. Although the retail business sector union can receive a higher rating on a CAEL model, defaults have often been reported. Therefore, a default prediction model is needed to support a CAEL model. As we have the default prediction model using a subdivision of indexes and statistical methods, it can be useful to have a prevention function through the estimation of the retail sector's default probability. Second, separating the difference between the finance and retail business sectors is necessary. Their businesses have different characteristics. Based on various management indexes that have been systematically managed by the National Fisheries Cooperative Federation of Korea, our model predicts retail default, and is better than the CAEL model in its failure prediction because it has various discriminative financial ratios reflecting the retail industry situation. Research design, data, and methodology - The model to predict retail default was presented using logistic analysis. To develop the predictive model, we use the retail financial statements of the NFCF. We consider 93 unions each year from 2006 to 2012 to select confident management indexes. We also adapted the statistical power analysis that is a t-test, logit analysis, AR (accuracy ratio), and AUROC (Area Under Receiver Operating Characteristic) analysis. Finally, through the multivariate logistic model, we show that it is excellent in its discrimination power and higher in its hit ratio for default prediction. We also evaluate its usefulness. Results - The statistical power analysis using the AR (AUROC) method on the short term model shows that the logistic model has excellent discrimination power, with 84.6%. Further, it is higher in its hit ratio for failure (prediction) of total model, at 94%, indicating that it is temporally stable and useful for evaluating the management status of retail institutions. Conclusions - This model is useful for evaluating the management status of retail union institutions. First, subdividing CAEL evaluation is required. The existing CAEL evaluation is underdeveloped, and discrimination power falls. Second, efforts to develop a varied and rational management index are continuously required. An index reflecting retail industry characteristics needs to be developed. However, extending this study will need the following. First, it will require a complementary default model reflecting size differences. Second, in the case of small and medium retail, it will need non-financial information. Therefore, it will be a hybrid default model reflecting financial and non-financial information.

• Journal of Intelligence and Information Systems
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• v.17 no.4
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• pp.241-254
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• 2011

Financial time-series forecasting is one of the most important issues because it is essential for the risk management of financial institutions. Therefore, researchers have tried to forecast financial time-series using various data mining techniques such as regression, artificial neural networks, decision trees, k-nearest neighbor etc. Recently, support vector machines (SVMs) are popularly applied to this research area because they have advantages that they don't require huge training data and have low possibility of overfitting. However, a user must determine several design factors by heuristics in order to use SVM. For example, the selection of appropriate kernel function and its parameters and proper feature subset selection are major design factors of SVM. Other than these factors, the proper selection of instance subset may also improve the forecasting performance of SVM by eliminating irrelevant and distorting training instances. Nonetheless, there have been few studies that have applied instance selection to SVM, especially in the domain of stock market prediction. Instance selection tries to choose proper instance subsets from original training data. It may be considered as a method of knowledge refinement and it maintains the instance-base. This study proposes the novel instance selection algorithm for SVMs. The proposed technique in this study uses genetic algorithm (GA) to optimize instance selection process with parameter optimization simultaneously. We call the model as ISVM (SVM with Instance selection) in this study. Experiments on stock market data are implemented using ISVM. In this study, the GA searches for optimal or near-optimal values of kernel parameters and relevant instances for SVMs. This study needs two sets of parameters in chromosomes in GA setting : The codes for kernel parameters and for instance selection. For the controlling parameters of the GA search, the population size is set at 50 organisms and the value of the crossover rate is set at 0.7 while the mutation rate is 0.1. As the stopping condition, 50 generations are permitted. The application data used in this study consists of technical indicators and the direction of change in the daily Korea stock price index (KOSPI). The total number of samples is 2218 trading days. We separate the whole data into three subsets as training, test, hold-out data set. The number of data in each subset is 1056, 581, 581 respectively. This study compares ISVM to several comparative models including logistic regression (logit), backpropagation neural networks (ANN), nearest neighbor (1-NN), conventional SVM (SVM) and SVM with the optimized parameters (PSVM). In especial, PSVM uses optimized kernel parameters by the genetic algorithm. The experimental results show that ISVM outperforms 1-NN by 15.32%, ANN by 6.89%, Logit and SVM by 5.34%, and PSVM by 4.82% for the holdout data. For ISVM, only 556 data from 1056 original training data are used to produce the result. In addition, the two-sample test for proportions is used to examine whether ISVM significantly outperforms other comparative models. The results indicate that ISVM outperforms ANN and 1-NN at the 1% statistical significance level. In addition, ISVM performs better than Logit, SVM and PSVM at the 5% statistical significance level.

• Journal of the Korean Geographical Society
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• v.37 no.5
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• pp.498-510
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• 2002

This study has the following two focuses to analyze the changes in national-level locational pattern of the U.S. professional sports franchises during 1950-2001. The first is to empirically clarify spatial orientation in the changing locational pattern of sports franchises. The second is to identify compared characteristics of the relocation cases reflecting the orientation to other cases, for the variables indicative of franchises' and leagues' pursuits of their relocation-related interests ultimately affecting franchises' relocations, by employing a legit model. As a result of the analyses, sports franchises and leagues, respectively have shown spatial orientation toward relocating to and toward locating new franchises in southern and western areas, responding to the changes in U.S. urbanization pattern. And, relocation cases reflecting the orientation have displayed a feature of the higher annual population growth rate in destination urban area than in origin area, in comparison to other cases.