• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.1
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• pp.83-93
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• 2020

The time delay is used as a major indicator of the level of traffic congestion on traffic crossroads. For this purpose, the Daechi Station intersection where traffic congestion occurs and the Yeongdong 5 Bridge intersection where the traffic condition is relatively good, and the average lag time based on the field survey with the lag time calculated various simulation programs. comparison of the average control delay of the field survey data the signal intersection analysis model the KHCS Dechi intersection 7.7 second / vehicle Young dong 5 bridge intersection 7.9 second / vehiclehe VISSIM showed a difference Dechi intersection 21.1 second / vehicle and Young dong 5 bridge intersection 8.1 second / vehiclehe T7F showed a difference Dechi intersection 3.3 second / vehicle and Young dong 5 bridge intersection 9.3 second / vehicle. Analyzing the same intersection proved that the results differed from one simulation model to another.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.11 no.3
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• pp.81-91
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• 2012

The world has been replacing fast fossil fuels vehicles with electric vehicles(EVs) to cope with climate change. The government set a goal which EVs will be substitute at least 10% of the domestic small vehicles with EVs until 2020, and will try to build electric charging infrastructures in apartments with the revision the law of 'the housing construction standards'. In apartments the EVs charging infrastructure and parking space is, essential to accomplish the goal. But the studies on EVs demand are few. In this study, we predicted that the demand for EVs using time-series analysis of statistical data, survey results for apartments residents in the metropolitan area. As a result, the ratio of the EVs appeared to be 6~21% for the total vehicles in a rental apartments for the years 2020, 21~39% in apartments for sales. For the EVs, the maximum power required for 1,000 households in rental apartment is predicted to be about 4200 kwh on a daily basis, while the maximum power in the apartment for sales is predicted to be 7800kwh.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.2
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• pp.273-278
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• 2010

A few small and medium enterprise administer its organization systematically, but most of them is affected by ability and level of a CEO rather than organization system. In this viewpoint, it can be said the study on ability and level of CEO in small and medium enterprise are so meaningful. Thus, in this paper, the core competency of CEO is obtained from the CEO through questionnaire and it is suggested the evaluation model of the CEO core competency. Also patterns were analyzed by ID3 and fuzzy ID3 from data on expert appraise for CEO core competency and level. The 'if-then' fuzzy rules and decision tree created by results of pattern analysis showed their usefulness for evaluation of CEO core competency in small and medium enterprise.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.3
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• pp.251-258
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• 2014

The purpose of the neural image analysis is to trace the velocities and the directions of moving mitochondria migrating through axons. This paper proposes an automated technique for detecting axon structure. Previously, the detection process has been carried out using a partially automated technique combined with some human intervention. In our algorithm, a consolidated image is built by taking the maximum intensity value on the all image frames at each pixel Axon detection is performed through vessel enhancement filtering followed by a peak detection procedure. In order to remove errors contained in ridge points, a filtering process is devised using a local reliability measure. Experiments have been performed using real neural image sequences and ground truth data extracted manually. It has been turned out that the proposed algorithm results in high detection rate and precision.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.3
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• pp.292-297
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• 2014

As a Social Network Service (SNS) has become an integral part of our everyday lives, millions of users can express their opinion and share information regardless of time and place. Hence sentiment analysis using micro-blogs has been studied in various field to know people's opinion on particular topics. Most of previous researches on movie reviews consider only positive and negative sentiment and use it to predict movie rating. As people feel not only positive and negative but also various emotion, the sentiment that people feel while watching a movie need to be classified in more detail to extract more information than personal preference. We measure sentiment distributions of each movie from tweets according to the Thayer's model. Then, we find similar movies by calculating similarity between each sentiment distributions. Through the experiments, we verify that our method using micro-blogs performs better than using only genre information of movies.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.2
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• pp.161-165
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• 2014

In this paper, we proposed the fuzzy prototype pattern classifier. In the proposed classifier, each prototype is defined to describe the related sub-space and the weight value is assigned to the prototype. The weight value assigned to the prototype leads to the change of the boundary surface. In order to define the prototypes, we use Fuzzy C-Means Clustering which is the one of fuzzy clustering methods. In order to optimize the weight values assigned to the prototypes, we use the Differential Evolutionary Algorithm. We use Linear Discriminant Analysis to estimate the coefficients of the polynomial which is the structure of the consequent part of a fuzzy rule. Finally, in order to evaluate the classification ability of the proposed pattern classifier, the machine learning data sets are used.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.7 no.1
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• pp.42-58
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• 2008

Nowadays the installation of Real-time Traffic Signal Control system is gradually spread, in order to solve the traffic problem which become serious. The most important thing are reliability of data collection and functionality of system in Real-time Traffic Signal Control System. But, the evaluation for those introduction system are defective after system constructing. So, many systems are not working properly to those systems's primarily purpose. This study is executed expansion through field test and analysis which check performance and advise of system operation. It has purpose to establish of the maintenance system of Real-time Traffic Signal Control system. As the result of analysis, we could find the several problems in this study. So, we also could guess that the effective maintenance systems of the Real-time Traffic Signal Control system is necessary within few years.

• Journal of the Korean Institute of Intelligent Systems
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• v.12 no.5
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• pp.385-392
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• 2002

Collaborative filtering method for personalization can suggest new items and information which a user hasn t expected. But there are some problems. Not only the steps for calculating similarity value between each user is complex but also it doesn t reflect user s interest dynamically when a user input a query. In this paper, classifying users by their interest makes calculating similarity simple. We propose the a1gorithm for readjusting user s interest dynamically using the profile and Bayesian learning. When a user input a keyword searching for a item, his new interest is readjusted. And the user s profile that consists of used key words and the presence frequency of key words is designed and used to reflect the recent interest of users. Our methods of adjusting user s interest using the profile and Bayesian learning can improve the real satisfaction of users through the experiment with data set, collected in University s library. It recommends a user items which he would be interested in.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.2
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• pp.191-196
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• 2015

There have been many studies on statistical forecasting on firm's performance and stock price by applying various financial indicators such as debt ratio and sales growth rate. Selecting predictors for constructing a prediction model among the various financial indicators is very important for precise prediction. Most of the previous studies applied variable selection algorithms for selecting predictors. However, the variable selection algorithm is considered to be at risk of eliminating certain amount of information from the indicators that were excluded from model construction. Therefore, we propose a firm's performance prediction model which principal component analysis is applied instead of the variable selection algorithm, in order to reduce dimensionality of input variables of the prediction model. In this study, we constructed the proposed prediction model by using financial data of American IT companies to empirically analyze prediction performance of the model.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.14 no.1
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• pp.13-21
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• 2015

This study focuses on operational analysis of 2 types of intersection shared lanes. First, the analysis showed that a through & right-turn shared lane is always less used than the adjacent through-only lanes and as a result, operational efficiency deteriorates. To improve the efficiency fine-tuning in signal timing optimization using lane-by-lane traffic volume data is required. Further improvement can be achieved by guiding drivers to equally use the shared lane. For left-turn & U-turn shared lanes, it was found that saturation flow rate is affected by interference between U-turn and conflicting right-turn movements. However, since such interference does not occur in every cycle, a statistical model must be established to develop realistic adjustment factor for saturation flow rate of the shared lane.