• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.10
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• pp.2201-2206
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• 2010

The shortage of fossil fuel drives researchers to find a new way to increases energy efficiency. In this paper, we propose a method to control the direction and speed of an air conditioner using a thermal image and fuzzy controlling method, which results in the increase of energy efficiency. The thermal image is first converted into a color temperature image which represents the temperature range from $24.0^{\circ}C$ to $27.0^{\circ}C$. The temperature image is divided into 5 columns and the distribution of them is used to analyze room temperature and control an air conditioner. The proposed method was applied to 300 by 400 thermal images. When the performance of the proposed method was compared to existing systems in energy efficiency, the proposed method was better than existing methods, which is clear from experimental results.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.4
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• pp.402-410
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• 2004

In this paper, an optimal design method of clonal selection based Fuzzy-Neural Networks (FNN) model for complex and nonlinear systems is presented. The FNNs use the simplified inference as fuzzy inference method and Error Back Propagation Algorithm as learning rule. Also Advanced Clonal Selection (ACS) is proposed to find the parameters such as parameters of membership functions, learning rates and momentum coefficients. The proposed method is based on an Immune Algorithm (IA) using biological Immune System and The performance is improved by control of differentiation rate. Through that procedure, the antibodies are producted variously and the parameter of FNN are optimized by selecting method of antibody with the best affinity against antigens such as object function and limitation condition. To evaluate the performance of the proposed method, we use the time series data for gas furnace and traffic route choice process.

• IEMEK Journal of Embedded Systems and Applications
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• v.4 no.4
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• pp.180-189
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• 2009

Currently, most automobile companies are interested in research on intelligent autonomous vehicle. They are mainly focused on driver's intelligent assistant and driver replacement. In order to develop an autonomous vehicle, lateral and longitudinal control is necessary. This paper presents a lateral and longitudinal control system for autonomous vehicle that has only mono-vision camera. For lane detection, we present a new lane detection algorithm using clothoid parabolic road model. The proposed algorithm in compared with three other methods such as virtual line method, gradient method and hough transform method, in terms of lane detection ratio. For adaptive control, we apply a vanishing point estimation to fuzzy control. In order to improve handling and stability of the vehicle, the modeling errors between steering angle and predicted vanishing point are controlled to be minimized. So, we established a fuzzy rule of membership functions of inputs (vanishing point and differential vanishing point) and output (steering angle). For simulation, we developed 1/8 size robot (equipped with mono-vision system) of the actual vehicle and tested it in the athletics track of 400 meter. Through the test, we prove that our proposed method outperforms 98 % in terms of detection rate in normal condition. Compared with virtual line method, gradient method and hough transform method, our method also has good performance in the case of clear, fog and rain weather.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.43 no.9 s.351
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• pp.142-148
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• 2006

Considering the domestic traffic environment and the increase of traffic accidents, we have been asked to exactly analyze the main causes of accidents for the accident-experienced drivers to be rehabilitated. In this thesis we present the development process and results of a driving simulator using the IPDE method in the interest of safe driving and driving rehabilitation. Through this Driving simulation development the rehabilitated driver has the possibility of experiencing the real driving situation with the driving aptitude and examines the reasons of accidents. Through the examinations the driver has the chance to correct the deformities of driving by choosing the explanatory scenes, and through this process the driver is able to develop the capability to react in the real situation. However this driving simulation system is one of the best developed, depending on weather and road condition the braking distance may change. Therefore the fuzzy rule and neural network have been used in this thesis to solve previously mentioned problem. The simulation exactly calculated the road and weather conditions to adjust the breaking intensity.

• 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 Korean Institute of Intelligent Systems
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• v.24 no.2
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• pp.147-154
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• 2014

In this study, chlorine modeling technique based on fuzzy system is proposed to reduce the carcinogenic substance and decide the optimal chlorine injection rate, which is affected by chlorine evaporation rate in sedimentation basin according to detention time, weather and water quality. The additional chlorine meter is installed in the inlet part of sedimentation to reduce the feedback time and implement cascade control, which leads to maintaining the residual chlorine concentration decided by fuzzy rule. It helps to take a preemptive action about long time delay, the characteristics of the disinfection process, and reduce the variation of residual chlorine rate by 7.3 times and the chlorine consumption by 40,000 dollars. It made a significant contribution to supply hygienically safe drinking water.

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.4
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• pp.304-309
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• 2013

This paper proposes a intelligent approach on range decision of figure of merit. Unknown range of the underwater target and the non-fixed signal excess make the uncertainty for the tracking process. Using the input data of signal excess related to the range, we establish the rule of the fuzzy set and the original data acquired by sonar can be transformed to the fuzzified data set. To reduce the error arisen from the unexpected data, we use the new data transformed in fuzzy set. The piecewise relations of the min value, max one, and the mean one are calculated. The three values are used for the expected range of the underwater target. By analysing the fluctuation of the data, we can expect the target's position and the characteristics of the maneuvering. The examples are presented to show the performance and the effectiveness of the proposed method.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.18 no.2
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• pp.172-179
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• 2006

This study developed a program for detecting charged refrigerant amount in system air-conditioner. System air-conditioner is an air-conditioning system with multiple indoor units. Due to the complexity of the system, it is more difficult to detect the refrigerant amount charged in the system air-conditioner than in a general single air-conditioner. Experiments were performed for a 6 HP outdoor unit with 3 indoor units in a psychrometric calorimeter. The experimental amount of the charged refrigerant was ranged from $60\%\;to\;140\%\;with\;10\%$ increasement. Fuzzy algorithm was employed for detecting the charged refrigerant amount in the system air-conditioner. The experimental data were used for curve-fitting for the general ranges of indoor and outdoor temperature conditions. Membership function was determined for the whole ranges of experimentally measured data and rule-bases were defined for each charged refrigerant amount. Developed program successfully predicted the measured data within $10\%$ resolution range.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.2
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• pp.219-224
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• 2017

These days, it is developed renewable energy-based wind power technology. Wind power generation is relatively quiet, and environmental damage is relatively low. In developed countries, a lot of wind power generation is being built. In Korea, the generation efficiency is low because there are few areas where the wind speed is maintained for four seasons. In recent years, forest damage, low noise, and environmental degradation complaints are frequent. In this paper, we performed an experiment to manage pitch control effectively by analyzing wind, direction, and temperature in real time based on FUZZY rule and cluster analysis.Using the new algorithm proposed by the simulation results, we could verify the efficiency of wind power generation pitch control for wind condition and direction condition by using the pitch control analysis technique.Furthermore, visualization representations have proven to automatically analyze early warning and efficiency of generator performance.