• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제4권4호
• /
• pp.575-594
• /
• 2010

In this study, we propose a space search algorithm (SSA) and then introduce a hybrid optimization of fuzzy inference systems based on SSA and information granulation (IG). In comparison with "conventional" evolutionary algorithms (such as PSO), SSA leads no.t only to better search performance to find global optimization but is also more computationally effective when dealing with the optimization of the fuzzy models. In the hybrid optimization of fuzzy inference system, SSA is exploited to carry out the parametric optimization of the fuzzy model as well as to realize its structural optimization. IG realized with the aid of C-Means clustering helps determine the initial values of the apex parameters of the membership function of fuzzy model. The overall hybrid identification of fuzzy inference systems comes in the form of two optimization mechanisms: structure identification (such as the number of input variables to be used, a specific subset of input variables, the number of membership functions, and polyno.mial type) and parameter identification (viz. the apexes of membership function). The structure identification is developed by SSA and C-Means while the parameter estimation is realized via SSA and a standard least square method. The evaluation of the performance of the proposed model was carried out by using four representative numerical examples such as No.n-linear function, gas furnace, NO.x emission process data, and Mackey-Glass time series. A comparative study of SSA and PSO demonstrates that SSA leads to improved performance both in terms of the quality of the model and the computing time required. The proposed model is also contrasted with the quality of some "conventional" fuzzy models already encountered in the literature.

• 한국소음진동공학회:학술대회논문집
• /
• 한국소음진동공학회 2007년도 추계학술대회논문집
• /
• pp.195-200
• /
• 2007

System identification of real-scale structure is performed using forced vibration test. There exist various techniques available for identifying the dynamic characteristis of structures using dynamic and static measurements. In this study, The finite element(FE) model of the structure is analytically constructed using ANSYS and the model was updated using the results experimentally measured by the forced vibration test. forced vibration tests showed that Hybrid Mass Damper induced floor responses coincided with the earthquake induced ones which was numerically calculated based on the updated FE model.

• Journal of Biosystems Engineering
• /
• 제33권3호
• /
• pp.196-203
• /
• 2008

Hybrid robust image processing algorithm to extract visual features of melon during the cultivation was developed based on a wireless tele-operative interface. Features of a melon such as size and shape including position were crucial to successful task automation and future development of cultivation data base. An algorithm was developed based on the concept of hybrid decision-making which shares a task between the computer and the operator utilizing man-computer interactive interface. A hybrid decision-making system was composed of three modules such as wireless image transmission, task specification and identification, and man-computer interface modules. Computing burden and the instability of the image processing results caused by the variation of illumination and the complexity of the environment caused by the irregular stem and shapes of leaves and shades were overcome using the proposed algorithm. With utilizing operator's teaching via LCD touch screen of the display monitor, the complexity and instability of the melon identification process has been avoided. Hough transform was modified for the image obtained from the locally specified window to extract the geometric shape and position of the melon. It took less than 200 milliseconds processing time.

• Structural Engineering and Mechanics
• /
• 제65권6호
• /
• pp.707-719
• /
• 2018

In this article, a new method is introduced to improve the local search capability of meta-heuristic algorithms using the projection of the path on the border of constraints. In a mathematical point of view, the Gradient Projection Method is applied through a new approach, while the imposed limitations are removed. Accordingly, the gradient vector is replaced with a new meta-heuristic based vector. Besides, the active constraint identification algorithm, and the projection method are changed into less complex approaches. As a result, if a constraint is violated by an agent, a new path will be suggested to correct the direction of the agent's movement. The presented procedure includes three main steps: (1) the identification of the active constraint, (2) the neighboring point determination, and (3) the new direction and step length. Moreover, this method can be applied to some meta-heuristic algorithms. It increases the chance of convergence in the final phase of the search process, especially when the number of the violations of the constraints increases. The method is applied jointly with the authors' newly developed meta-heuristic algorithm, entitled Star Graph. The capability of the resulted hybrid method is examined using the optimal design of truss and frame structures. Eventually, the comparison of the results with other meta-heuristics of the literature shows that the hybrid method is successful in the global as well as local search.

• 한국정보과학회논문지:정보통신
• /
• 제34권6호
• /
• pp.483-492
• /
• 2007

본 논문에서는 RFID 시스템에서 쿼리 트리 기반의 태그 충돌 중재를 위한 새로운 프로토콜을 제안한다. 제안한 하이브리드 쿼리 트리(Hybrid Query Tree) 기법은 이진 쿼리 트리 대신에 4-ary 쿼리 트리를 이용하여 태그 충돌 수를 줄였으며 추가적으로 발생하는 유휴 시간을 줄이기 위해 slotted 백오프 기법을 활용하였다. 실험결과 및 수학적 분석은 제안한 하이브리드 쿼리 트리 프로토콜이 기존에 제시된 기법보다 우수한 성능을 보임을 입증한다.

• 한국통신학회논문지
• /
• 제32권4A호
• /
• pp.358-364
• /
• 2007

RFID(Radio Frequency IDentification) 기술은 라디오 주파수를 사용하는 비접촉 자동인식 기술이다. 이런 RFID 기술의 확산을 위해서는 리더(reader)가 다수의 태그(tag)를 짧은 시간 안에 인식하는 다중 태그 식별 문제를 해결 해야만 한다. 지금까지 이 문제를 해결하기 위한 충돌 방지(anti-collision) 알고리즘이 많이 개발되었고 이것들은 크게 알로하(ALOHA) 기반 알고리즘과 트리(tree) 기반 알고리즘으로 나뉜다. 본 논문에서는 이 두 가지 방법의 특징을 혼합한 새로운 충돌 방지 알고리즘 2가지를 제안한다. 그리고 대표적인 충돌 방지 알고리즘인 18000-6 Type A, Type B, Type C, query tree 알고리즘과 성능 비교 및 평가를 한다.

• 한국통신학회논문지
• /
• 제33권10A호
• /
• pp.987-996
• /
• 2008

본 논문에서는 기존 리더 충돌방지 알고리즘인 Channel Monitoring 알고리즘, Pulse Protocol 알고리즘에 대하여 살펴보고, 태그인식시간을 감소시키고, 데이터 처리량, 시스템 효율을 증가 시킬 수 있는 슬롯 점유확률을 이용한 Pulse Protocol 기반의 Hybrid 리더 충돌 방지 알고리즘을 제안한다. 제안하는 알고리즘은 Pulse Protocol 알고리즘의 성능을 향상시키기 위하여 Channel Monitoring 알고리즘에서 사용되고 있는 슬롯의 점유확률 (Occupied Probability)을 이용한다. 즉, 리더들은 랜덤 backoff 시간을 생성한 후, 자신이 사용하게 될 슬롯의 점유확률을 확인하고, 이 슬롯의 점유확률이 0보다 크다면, 새로운 랜덤 backoff 시간을 생성하여 리더간의 충돌을 피한다. 기존 알고리즘들과 제안하는 알고리즘과의 성능을 태그인식시간, 데이터 처리량 및 시스템 효율 등의 성능분석항목들을 통하여 비교 및 분석하여, 제안하는 알고리즘에 의하여 리더의 개수가 증가함에 따라 7% 정도의 태그인식시간 및 데이터 처리량 성능 향상을 확인한다.

• Journal of Information Processing Systems
• /
• 제15권2호
• /
• pp.422-432
• /
• 2019

A hybrid kernel function of support vector machine is proposed to improve the classification performance of power quality disturbances. The kernel function mathematical model of support vector machine directly affects the classification performance. Different types of kernel functions have different generalization ability and learning ability. The single kernel function cannot have better ability both in learning and generalization. To overcome this problem, we propose a hybrid kernel function that is composed of two single kernel functions to improve both the ability in generation and learning. In simulations, we respectively used the single and multiple power quality disturbances to test classification performance of support vector machine algorithm with the proposed hybrid kernel function. Compared with other support vector machine algorithms, the improved support vector machine algorithm has better performance for the classification of power quality signals with single and multiple disturbances.

• Smart Structures and Systems
• /
• 제14권6호
• /
• pp.1105-1129
• /
• 2014

The unscented Kalman filter (UKF) has been developed for nonlinear model parametric identification, and it assumes that the model parameters are symmetrically distributed about their mean values without any constrains. However, the parameters in many applications are confined within certain ranges to make sense physically. In this paper, a constrained unscented Kalman filter (CUKF) algorithm is proposed to improve accuracy of numerical substructure modeling in hybrid testing. During hybrid testing, the numerical models of numerical substructures which are assumed identical to the physical substructures are updated online with the CUKF approach based on the measurement data from physical substructures. The CUKF method adopts sigma points (i.e., sample points) projecting strategy, with which the positions and weights of sigma points violating constraints are modified. The effectiveness of the proposed hybrid testing method is verified by pure numerical simulation and real-time as well as slower hybrid tests with nonlinear specimens. The results show that the new method has better accuracy compared to conventional hybrid testing with fixed numerical model and hybrid testing based on model updating with UKF.

• 정보처리학회논문지A
• /
• 제15A권5호
• /
• pp.287-294
• /
• 2008

RFID 시스템에서 리더와 태그는 단일 무선 공유 채널을 갖기 때문에 RFID 수동형 태그를 위한 태그 충돌 중재가 태그 인식을 위한 중요한 이슈이다. 본 논문에서는 태그 충돌 방지를 위한 하이브리드 하이퍼 쿼리 트리 알고리즘($H^{2}QT$, Hybrid Hyper Query Tree)을 제안한다. 제안된 알고리즘은 쿼리 트리를 기반으로 태그가 리더에게 ID를 전송하는 시점을 전송ID 상위 3비트 내의 '1'값을 이용하여 결정한다. 또한 전송 받은 Tag의 상위 3비트는 충돌이 발생하더라도 전송 슬롯에 따라 다르므로 제안한 알고리즘에서 예측이 가능하다. 시뮬레이션을 통한 성능 평가에서 다른 트리 기반 프로토콜에 비해 제안한 알고리즘이 쿼리 횟수에서 높은 성능을 갖는다는 것을 보여준다.