• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권9호
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• pp.4271-4294
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• 2018

Communication cost is the most important factor in Wireless Sensor Networks (WSNs), as exchanging control keying messages consumes a large amount of energy from the constituent sensor nodes. Time-based Dynamic Keying and En-Route Filtering (TICK) can reduce the communication costs by utilizing local time values of the en-route nodes to generate one-time dynamic keys that are used to encrypt reports in a manner that further avoids the regular keying or re-keying of messages. Although TICK is more energy efficient, it employs no re-encryption operation strategy that cannot determine whether a healthy report might be considered as malicious if the clock drift between the source node and the forwarding node is too large. Secure SOurce-BAsed Loose Synchronization (SOBAS) employs a selective encryption en-route in which fixed nodes are selected to re-encrypt the data. Therefore, the selection of encryption nodes is non-adaptive, and the dynamic network conditions (i.e., The residual energy of en-route nodes, hop count, and false positive rate) are also not focused in SOBAS. We propose an energy efficient selection of re-encryption nodes based on fuzzy logic. Simulation results indicate that the proposed method achieves better energy conservation at the en-route nodes along the path when compared to TICK and SOBAS.

• 한국건설관리학회:학술대회논문집
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• 한국건설관리학회 2001년도 학술대회지
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• pp.519-524
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• 2001

국내·외적으로 건설공사의 리스크관리에 대한 중요성은 더욱 커져가고 있지만, 합리적인 리스크인자의 구축방법과 개별 리스크인자의 분석 및 정량화가 용이하지 않기 때문에 실무적 운용이 가능한 리스크분석시스템을 구축한 경우는 극히 미흡한 실정이다. 본 연구에서는 전문가의 주관적 판단과 언어적 변량을 이용하여 리스크를 정량화하기 위한 퍼지분석방법을 제시한다. 본 퍼지분석방법은 건설공사의 리스크인자를 발생확률 발생강도, 발생빈도로 구분하여 평가하게 함으로서 그 적용성과 정확성을 높일 수 있도록 하였고, 언어적 변량을 이용하여 리스크를 정량화하기 때문에 복잡한 자료의 구축과 분석시간을 단축하였으며, 그 적용이 매우 쉽다는 장점을 갖게 된다.

• Journal of Electrical Engineering and Technology
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• 제13권2호
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• pp.822-828
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• 2018

AC-DC conversion is a necessary for the systems that require DC source. This conversion has been done via rectifiers based on controlled or uncontrolled semiconductor switches. Advances in the power electronics and microprocessor technologies allowed the use of Pulse Width Modulation (PWM) rectifiers. In this paper, dq-axis current and DC link voltage of three-phase PWM rectifier are controlled by using type-2 fuzzy neural network (T2FNN) controller. For this aim, a simulation model is built by MATLAB/Simulink software. The model is tested under three different operating conditions. The parameters of T2FNN is updated online by using back-propagation algorithm. The results obtained from both T2FNN and Proportional + Integral + Derivate (PID) controller are given for three operating conditions. The results show that three-phase PWM rectifier using T2FNN provides a superior performance under all operating conditions when compared with PID controller.

• 한국안전학회지
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• 제29권4호
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• pp.184-190
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• 2014

Decommissioning process of nuclear facilities consist of a sequence of problem solving activities, because there may exist not only working environments contaminated by radiological exposure but also industrial hazards such as fire, explosions, toxic materials, and electrical and physical hazards. Therefore, not a few countries in the world have been trying to develop appropriate counter techniques in order to guarantee safety and efficiency of the process. In spite of that, there still exists neither domestic nor international standard. Unfortunately, however, there are few workers who experienced decommissioning operations a lot in the past. As a solution, it is quite necessary to utilize experts' opinions for risk assessment in decommissioning process. As for an individual hazard factor, risk assessment techniques are getting known to industrial workers with advance of safety technology, but the way how to integrate those results is not yet. This paper aimed to find out an appropriate technique to integrate individual risk assessment results from the viewpoint of experts. Thus, on one hand the whole risk assessment activity for decommissioning operations was modeled as a sequence of individual risk assessment steps which can be classified into two activities, decontamination and dismantling, and on the other, a risk assessment structure was introduced. The whole model was inferred with Fuzzy theory and techniques, and a numerical example was appended for comprehension.

• Earthquakes and Structures
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• 제24권6호
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• pp.429-437
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• 2023

This paper studied the prediction of structural damage indices to buildings after earthquake occurrence using Multiple Linear Regression (MLR) and Fuzzy Linear Regression (FLR) methods. Particularly, the structural damage degree, represented by the Maximum Inter Story Drift Ratio (MISDR), is an essential factor that ensures the safety of the building. Thus, the seismic response of a steel building was evaluated, utilizing 65 seismic accelerograms as input signals. Among the several response quantities, the focus is on the MISDR, which expresses the postseismic damage status. Using MLR and FLR methods and comparing the outputs with the corresponding evaluated by nonlinear dynamic analyses, it was concluded that the FLR method had the most accurate prediction results in contrast to the MLR method. A blind prediction applying a set of another 10 artificial accelerograms also examined the model's effectiveness. The results revealed that the use of the FLR method had the smallest average percentage error level for every set of applied accelerograms, and thus it is a suitable modeling tool in earthquake engineering.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2000년도 추계학술대회 학술발표 논문집
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• pp.33-36
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• 2000

Recently, in the shipping companies have been employing prudently in order to prevent from sea accidents occurred by human factors. Also the students of merchant marine universities are choosing prudently the shipping companies when taking a job. But many qualitative and quantitative factors are considered in decision making for the employment. FSM(Fuzzy Structural Modeling) has been widely used in modeling the system composed of such qualitative and quantitative factor. In this paper, a case study is discussed for the analysis of the consciousness of the employment of shipping companies using FSM. Also this paper proposed the planes for educating and recruitment guiding the student in maritime university.

• 한국정보통신학회논문지
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• 제4권3호
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• pp.603-610
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• 2000

본 논문에서는 직접 적응제어기와 간접 적응제어기를 Lyapunov 안정도 이론에 근거하여 결합하였다. 제어기는 RBF 신경망을 이용하여 구성하였으며 하중파라미터들은 적응칙에 의하여 조정되도록 하였다. 또한 시스템의 성능에 영향을 미치는 결합 가중치는 퍼지 If-THEN 규칙을 이용하여 결정되도록 하였다. 이렇게 함으로써 직접 적응제어기와 간접 적응제어기의 장점을 지니는 직 간접 혼합 신경망 적응제어기를 구성할 수 있었다. 제안한 알고리즘의 효용성을 보이기 위하여 일축 강페 로봇 매니퓰레이터를 대상으로 시뮬레이션한 결과 만족할 만한 성능을 보였다.

• Industrial Engineering and Management Systems
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• 제6권2호
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• pp.106-118
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• 2007

This paper present a new optimization model to generate aggregate production planning by considering electric cost. The new Time Of Switching (TOS) electric type is introduced by switching over Time Of Day (TOD) and Time Of Use (TOU) electric types to minimize the electric cost. The fuzzy demand and Dynamic inventory tracking with multiple plant capacity are modeled to cover the uncertain demand of customer. The constraint for minimum hour limitation of plant running per one start up event is introduced to minimize plants idle time. Furthermore; the Optimal Weight Moving Average Factor for customer demand forecasting is introduced by monthly factors to reduce forecasting error. Application is illustrated for multiple cement mill plants. The mathematical model was formulated in spreadsheet format. Then the spreadsheet-solver technique was used as a tool to solve the model. A simulation running on part of the system in a test for six months shows the optimal solution could save 60% of the actual cost.

• 한국산업융합학회 논문집
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• 제21권3호
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• pp.125-131
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• 2018

In this paper, we propose a homogeneous multisensor-based navigation algorithm for a mobile robot, which is intelligently searching the goal location in unknown dynamic environments with moving obstacles using multi-ultrasonic sensor. Instead of using "sensor fusion" method which generates the trajectory of a robot based upon the environment model and sensory data, "command fusion" method by fuzzy inference is used to govern the robot motions. The major factors for robot navigation are represented as a cost function. Using the data of the robot states and the environment, the weight value of each factor using fuzzy inference is determined for an optimal trajectory in dynamic environments. For the evaluation of the proposed algorithm, we performed simulations in PC as well as real experiments with mobile robot, AmigoBot. The results show that the proposed algorithm is apt to identify obstacles in unknown environments to guide the robot to the goal location safely.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2001년도 합동 추계학술대회 논문집 정보 및 제어부문
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• pp.420-423
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• 2001

In this paper, the Multi-FNNs(Fuzzy-Neural Networks) architecture is identified and optimized using HCM(Hard C-Means) clustering method and genetic algorithms. The proposed Multi-FNNs architecture uses simplified inference and linear inference as fuzzy inference method and error back propagation algorithm as learning rules. Here, HCM clustering method, which is carried out for the process data preprocessing of system modeling, is utilized to determine the structure of Multi-FNNs according to the divisions of input-output space using I/O process data. Also, the parameters of Multi-FNNs model such as apexes of membership function, learning rates and momentum coefficients are adjusted using genetic algorithms. An aggregate performance index with a weighting factor is used to achieve a sound balance between approximation and generalization abilities of the model. To evaluate the performance of the proposed model we use the time series data for gas furnace and the NOx emission process data of gas turbine power plant.