• Journal of the Korean Institute of Intelligent Systems
• /
• v.11 no.3
• /
• pp.231-240
• /
• 2001

Conventional expert systems has been criticized due to its lack of capability to adapt to the changing decision-making environments. In literature, many methods have been proposed to make expert systems more environment-adaptive by incorporating fuzzy logic and neural networks. The objective of this paper is to propose a new approach to building a self-evolving expert system inference mechanism by integrating fuzzy neural network and fuzzy rule extraction technique. The main recipe of our proposed approach is to fuzzify the training data, train them by a fuzzy neural network, extract a set of fuzzy rules from the trained network, organize a knowledge base, and refine the fuzzy rules by applying a pruning algorithm when the decision-making environments are detected to be changed significantly. To prove the validity, we tested our proposed self-evolving expert systems inference mechanism by using the bankruptcy data, and compared its results with the conventional neural network. Non-parametric statistical analysis of the experimental results showed that our proposed approach is valid significantly.

• Journal of Electrical Engineering and Technology
• /
• v.13 no.2
• /
• pp.961-968
• /
• 2018

Recently, researches on automatic recognition of human activities have been actively carried out with the emergence of various intelligent systems. Since a large amount of visual data can be secured through Closed Circuit Television, it is required to recognize human behavior in a dynamic situation rather than a static situation. In this paper, we propose new intelligent human activity recognition model using the trajectory information extracted from the video sequence. The proposed model consists of three steps: segmentation and partitioning of trajectory step, feature extraction step, and behavioral learning step. First, the entire trajectory is fuzzy partitioned according to the motion characteristics, and then temporal features and spatial features are extracted. Using the extracted features, four pedestrian behaviors were modeled by decision tree learning algorithm and performance evaluation was performed. The experiments in this paper were conducted using Caviar data sets. Experimental results show that trajectory provides good activity recognition accuracy by extracting instantaneous property and distinctive regional property.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.5 no.4
• /
• pp.347-352
• /
• 2005

PD(Partial discharges) are small electrical sparks that occur within the electric insulation of cables, transformers and windings on motors. PD analysis is a proactive diagnostic approach that uses PD measurements to evaluate the integrity of this equipment. Recently, several diagnostic algorithms for classifying the type of PD and locating the defect position have been developed. In this work, a new PD recognition system is proposed, which utilizes approximate coefficients of wavelet transform as a feature vector, furthermore, introduces bank of Elman networks to recognize the various PD phenomena. In order to verify the performance of the proposed scheme, it is applied to the simulated PD data.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.11 no.3
• /
• pp.264-269
• /
• 2001

In this paper, we interpret a score as a time series and deal with the fuzzy logic-based modeling of it. The musical notes in a score represent a lot of information about the length of a sound and pitches, etc. In this paper, using melodies, tones and pitches in a score, we transform data on a score into a time series. Once more, we foml the new Lime series by sliding a window through the time series. For analyzing the time series data, we make use of the Box-Jenkins s time series analysis. On the basis of the identified characteristics of time series, we construct the fuzzy model.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 2001.05a
• /
• pp.211-214
• /
• 2001

In this paper, we interpret a score as a time series and deal with the fuzzy logic-based modeling of it. The musical notes in a score represent a lot of information about the length of a sound and pitches, etc. In this paper, using melodies, tones and pitches in a score, we transform data on a score into a time series. Once more, we form the new time series by sliding a window through the time series. For analyzing the time series data, we make use of the Box-Jenkinss time series analysis. On the basis of the identified characteristics of time series, we construct the fuzz model.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.16 no.1
• /
• pp.50-63
• /
• 2017

While transit is inconvenient, it is also inevitable for the efficient public transportation. Reducing the number of transfers as much as possible is most important in providing the convenience of public transportation and facilitating the public transportation. As for the public transportation card data, 61,986 items on weekdays and 69,100 items on weekends were collected. Pattern analysis and traffic influence factors were analyzed using traffic data card. Trip chain results revealed that people have more transit transfers for shopping and leasure than commuting purposes on weekends and that commuting distance and time increase by 10 km and 9.9 minutes, respectively. Besides, results of the structural equation model showed that factor 1(total travel time, total travel distance), factor 2(number of people getting on and off), factor 3(transit time), and factor 4(number of bus connections, number of operations) were found to have significant effects on the number of transfers.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.16 no.5
• /
• pp.60-71
• /
• 2017

The purpose of this study is to evaluate vertical moving facilities at subway stations for the elderly users and to analyze their improvement measures. To evaluate vertical moving facilities of the top 31 subway stations with the most trips in Seoul, a data envelopment analysis (DEA) is employed. The input variables for the DEA include the number and percentage of elderly users, which are calculated using smart card data. the output variables consist of the number of elevators and escalators per 100 steps. The results show that the average score of 31 subway stations is 0.62 and four stations, i.e., Jamsil, Gasan Complex, Konkuk University, and Dongmyo, have the highest score. These four subway stations are set as benchmarking groups for the other stations with the lower score. Based on the comparison with the benchmarking groups, the improvement measures for vertical moving facilities of each station are suggested and discussed.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.25 no.3
• /
• pp.242-247
• /
• 2015

In this study, we propose the design of Radial Basis Function Neural Network(RBFNN) classifier in order to classify between precipitation and non-precipitation echo. The characteristics of meteorological radar data is analyzed for classifying precipitation and non-precipitation echo. Input variables is selected as DZ, SDZ, VGZ, SPN, DZ_FR, VR by performing pre-processing of UF data based on the characteristics analysis and these are composed of training and test data. Finally, QC data being used in Korea Meteorological Administration is applied to compare with the performance results of proposed classifier.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
• /
• v.13 no.1
• /
• pp.69-76
• /
• 1999

This paper proposed a design of intelligent supervisory control systems for maintenance of highway traffic information equiprrent and processing algorithm of equiprrent fault data. The fault data of highway traffic equipment are transmitted from rerrnte supervisory controller to central supervisory system by real time, the transmitted fault data are anaIyzed the characteristic using evaluation algorithm of fault data in central supervisory system. The evaluation algorithm includes a neural network and fault knowlOOge-base for processing the multi-generated fault data. For validating the evaluation algorithm of intelligent supervisory control systems, the rrethod of analysis used to the five pattern of binary signal by transmitted real time and the opTclting user-interface constructed in central supervisory system.

• Communications for Statistical Applications and Methods
• /
• v.8 no.2
• /
• pp.531-541
• /
• 2001

In this study, we compare the capabilities of the data mining tools of the most updated version objectively and provide the useful information in which enterprises and universities chose them. In particular, we compare the SAS/Enterprise Miner 3.0, SPSS/Clementine 5.2 and IBM/Intelligent Miner 6.1 which are well known and easily gotten.