• The Transactions of the Korean Institute of Power Electronics
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• v.10 no.1
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• pp.45-51
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• 2005

This paper presents a comparison of rotor position estimation of a switched reluctance motor(SRM) with built-in search coils by three methods. The search coil EMFs are not generated in the SRM with built-in search coils at standstill. So an initial rotor position estimation method is needed. In this paper squared euclidean distance, fuzzy logic and neural network methods we proposed for the estimation of initial rotor position. The simulated results of the three methods are compared. The simulated result of the squared euclidean distance method, which has the best performance, is supported by the experimental result.

• Journal of Biomedical Engineering Research
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• v.29 no.1
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• pp.17-24
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• 2008

The aim of this paper is to report our preliminary results of investigating the spatial focalization of Zen-meditation EEG (electroencephalograph) in alpha band (8-13 Hz). For comparison, the study involved two groups of subjects, practitioners (experimental group) and non-practitioners (control group). To extract EEG alpha rhythm, wavelet analysis was applied to multi-channel EEG signals. Normalized alpha-power vectors were then constructed from spatial distribution of alpha powers, that were classified by Fuzzy C-means based algorithm to explore various brain spatial characteristics during meditation (or, at rest). Optimal number of clusters was determined by correlation coefficients of the membership-value vectors of each cluster center. Our results show that, in the experimental group, the incidence of frontal alpha activity varied in accordance with the meditation stage. The results demonstrated three different spatiotemporal modules consisting with three distinctive meditation stages normally recognized by meditation practitioners. The frontal alpha activity in two groups decreased in different ways. Particularly, monotonic decline was observed in the control group, and the experimental group showed increasing results. The phenomenon might imply various mechanisms employed by meditation and relaxation in modulating parietal alpha.

• Proceedings of the KIPE Conference
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• 2012.07a
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• pp.359-360
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• 2012

This paper proposes a scheme of auto-tuning fuzzy PI controller and input voltage feed forward to control the output voltage of a three-phase Z-source inverter (ZSI). The proposed scheme adjusts the ts (Kp and Ki) in real time in order to find the most suitable Kp and Ki for PI controller and to simplify the controller design. The proposed scheme is verified the validity by experiment and co-simulation in PSIM and MATLAB/SIMULINK both load step change and input DC voltage variation in Z-source inverter, and has compared with the conventional PID control scheme. The experiment results involve of three-phase output voltage, Z-network capacitor voltage and dc-link peak voltage value. By those analysis and comparison, the availability of the proposed method in output voltage transient response quality improving has been verified. Compared with conventional PID method, the proposed method showed a more effective and robust control performance for coping with the severe disturbance conditions.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.1
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• pp.38-59
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• 2022

Web services instances can be classified into two categories, namely trusted and untrusted from users. A web service with high throughput (TP) and low response time (RT) instance values is a trusted web service. Web services are not trustworthy due to the mismatch in the guaranteed instance values and the actual values achieved by users. To perform web services selection from users' attained TP and RT values, we need to verify the correct prediction of trusted and untrusted instances from invoked web services. This accurate prediction of web services instances is used to perform the selection of web services. We propose to construct fuzzy rules to label web services instances correctly. This paper presents web services selection using a well-known machine learning algorithm, namely REPTree, for the correct prediction of trusted and untrusted instances. Performance comparison of REPTree with five machine learning models is conducted on web services datasets. We have performed experiments on web services datasets using a ten k-fold cross-validation method. To evaluate the performance of the REPTree classifier, we used accuracy metrics (Sensitivity and Specificity). Experimental results showed that web service (WS1) gained top selection score with the (47.0588%) trusted instances, and web service (WS2) was selected the least with (25.00%) trusted instances. Evaluation results of the proposed web services selection approach were found as (asymptotic sig. = 0.019), demonstrating the relationship between final selection and recommended trust score of web services.

• Journal of Korean Society of Forest Science
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• v.99 no.6
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• pp.802-807
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• 2010

The objective of this study was to estimate potential of domestic long-term wood supply by using fuzzy linear programming (FLP). In order to construct a numerical formula model, maximization of total timber production was used for the objective function. Size limit of harvesting and sustained yield were used as the constraints. The results of comparison between LP and FLP were shown that LP is more suitable than FLP in terms of the amount of timber production and final forest stock. However, as long-term sustained yield was limitedly achieved by using LP, FLP was more desirable for prediction of potential wood supply. According to the results of this study, the potential of annual domestic wood supply was estimated about 10.5 million cubic meters. Gyeong buk, Jeon nam, Gangwon and Gyeong nam province were highly ranked in order of provincial potential of wood supply.

• Proceedings of the Korean Society for Rock Mechanics Conference
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• 2000.09a
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• pp.171-181
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• 2000

Many Studies of tunnel and tunnelling safety have been developed continuously based on the increasing social interests in underground space since 1990's in Korea. Because the growth of population in metropolitan has been accelerated at a faster pace than the development of the cities, underground facilities have been created as a great extent in view of less land space available. In this study, a lot of types of tunnel failure were surveyed and the detail causes were studied after many cases of tunnel failure were collected. There were suggested brief countermeasure of tunnel failure through case study. An expert system was developed to predict the safety of tunnel and choose proper tunnel reinforcement system using fuzzy quantification theory and fuzzy inference rule based on tunnel information database. The comparison result between the predicted reinforcement system level and measured ones was very similar. In-situ data were obtained in three tunnel sites including subway tunnel under Han river. This system will be very helpful to make the most of in-situ data and suggest proper applicability of tunnel reinforcement system developing more resonable tunnel support method from dependance of some experienced experts for the absent of guide.

• Tunnel and Underground Space
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• v.10 no.3
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• pp.418-429
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• 2000

Many Studies of tunnel and tunnelling safety have been developed continuously based on the increasing social interests in underground space since 1990's in Korea. Because the growth of population in metropolitan has been accelerated at a faster pace than the development of the cities, underground facilities have been created as a great extent in view of less land space available. In this study, a lot of types of tunnel failure were surveyed and the detail causes were studied after many cases of tunnel failure were collected. There were suggested brief countermeasure of tunnel failure through case study. An expert system was developed to predict the safety of tunnel and choose proper tunnel reinforcement system using fuzzy quantification theory and fuzzy inference rule based on tunnel information database. The comparison result between the predicted reinforcement system level and measured ones was very similar. In-situ data were obtained in three tunnel sites including subway tunnel under Han river. This system will be very helpful to make the most of in-situ data and suggest proper applicability of tunnel reinforcement system developing more resonable tunnel support method from dependance of some experienced experts for the absent of guide.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.24 no.2
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• pp.157-165
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• 2011

Base isolation system is widely used for reduction of dynamic responses of structures subjected to seismic load. Recently, research on a smart base isolation system that can effectively reduce dynamic responses of the isolated structure without accompanying increases in base drifts has been actively conducted. In this study, a smart base isolation system was applied to an arch structure subjected to seismic excitation and its control performance for reduction of seismic responses was evaluated. In order to make a smart base isolation system, 4kN MR dampers and low damping elastomeric bearings were used. Seismic response control performance of the proposed smart base isolation system was compared to that of the optimally designed lead-rubber bearing(LRB) isolation system. To this end, an artificial ground motion developed based on KBC2009 design response spectrum was used as a seismic excitation. Fuzzy control algorithm was used to control MR damper in the smart base isolation system and multi-objective genetic algorithm was employed to optimize the fuzzy controller. Based on numerical simulation results, it has been shown that the smart base isolation system can drastically reduce base drifts and seismic responses of the example arch structure in comparison with LRB isolation system.

• Journal of the Korean Institute of Intelligent Systems
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• v.12 no.5
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• pp.467-472
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• 2002

In this paper, we propose a Fuzzy Cellular Neural Network(FCNN) that is based on a-Least Trimmed Square Hausdorff distance(a-LTSHD) which applies Hausdorff distance(HD) to the FCNN structure in order to remove the impulse noise of images effectively and also improve the speed of operation. FCNN incorporates Fuzzy set theory to Cellular Neural Network(CNN) structure and HD is used as a scale which computes the distance between set or two pixels in binary images without confrontation of the feature object. This method has been widely used with the adjustment of the object. For performance evaluation, our proposed method is analyzed in comparison with the conventional FCNN, with the Opening-Closing(OC) method, and the LTSHD based FCNN by using Mean Square Error(MSE) and Signal to Noise Ratio(SNR). As a result, the performance of our proposed network structure is found to be superior to the other algorithms in the removal of impulse noise.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.11 no.1
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• pp.23-28
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• 2011

In this paper, we propose a channel selection scheme for secondary users in cognitive radio sensor networks, which includes learning automata and fuzzy logic system (FLS). In the proposed scheme, FLS is used as the channel selection mechanism while the learning automata algorithm is being used to learn the radio environment such as channel link quality. Signal to noise ratio of the link between primary user (PU) and secondary user (SU), the probability of choosing channel, and signal to noise ratio of the link between secondary users are chosen as input parameters for the FLS to decide one data channel among multiple channels. Simulation results show that the proposed scheme does indeed provide advantages in improving the throughput of CR networks, in comparison with some other previous schemes.