• 산업경영시스템학회지
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• 제34권2호
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• pp.112-120
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• 2011

The early phase of design intrinsically contains multiple sources of uncertainty in describing design, and nevertheless the decision-making process at this phase exerts a critical effect upon drawing a successful design. This paper proposes a set-based design approach for multi-objective design problem under uncertainty. The proposed design approach consists of four design processes including set representation, set propagation, set modification, and set narrowing. This approach enables the flexible and robust design while incorporating designer's preference structure. In contrast to existing optimization techniques, this approach generates a ranged set of design solutions that satisfy changing sets of performance requirements.

• 산업경영시스템학회지
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• 제34권3호
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• pp.90-96
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• 2011

Finding the critical path (or the longest path) on acyclic directed graphs, which is well-known as PERT/CPM, the ambiguity of each acr's length can be modeled as a range or an interval, in which the actual length of arc may realize. In this case, the min-max regret criterion, which is widely used in the decision making under uncertainty, can be applied to find the critical path minimizing the maximum regret in the worst case. Since the min-max regret critical path problem with the interval arc's lengths is known as NP-hard, this paper proposes a heuristic algorithm to diminish the maximum regret. Then the computational experiments shows the proposed algorithm contributes to the improvement of solution compared with the existing heuristic algorithms.

• 국제학술발표논문집
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• The 4th International Conference on Construction Engineering and Project Management Organized by the University of New South Wales
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• pp.597-602
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• 2011

A robust asset management methodology is essential for effective decision-making of maintenance, repair and rehabilitation of a bridge network. It can be achieved by a computer-based bridge management system (BMS). Successful BMS development requires a reliable bridge deterioration model, which is the most crucial component in a BMS, and an optimal management philosophy. The maintenance optimization methodology proposed in this paper is developed for a small bridge network with limited structural condition rating records. . The methodology is organized in three major components: (1) bridge health index (BHI); (2) maintenance and budget optimization; and (3) reliable Artificial Intelligence (AI) based bridge deterioration model. The outcomes of the paper will help to identify BMS implementation problems and to provide appropriate solutions for managing small bridge networks.

• 시스템엔지니어링학술지
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• 제20권1호
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• pp.76-84
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• 2024

This study investigates the design of an optical observation system for continuously tracking unknown space object targets within the telescope's field of view at a short cycle rate of several to tens of frames per second. Through modeling and integrated simulation by design variables, we aim to identify combinations that satisfy the performance effectiveness scale. The study demonstrates the effectiveness of a model-based simulation analysis approach in rapidly identifying design parameters that meet specific performance requirements. By leveraging numerical models tailored to the desired performance analysis level, the approach provides a robust foundation for decision-making, eliminating reliance on empirical methods or vague estimations.

• 대한기계학회논문집A
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• 제26권10호
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• pp.2073-2081
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• 2002

In product design and manufacturing, axiomatic design provides a systematic approach for the decision-making process. Two axioms have been defined such as the Independence Axiom and the Information Axiom. The Information Axiom states that the best design among those that satisfy the independence axiom is the one with the least information content. In other words, the best design is the one that has the highest probability of success. On the other hand, the Taguchi robust design is used in the two-step process; one is "reduce variability," and the other is "adjust the mean on the target." The two-step can be interpreted as a problem that has two FRs (functional requirements). Therefore, the Taguchi method should be used based on the satisfaction of the Independence Axiom. Common aspects exist between the Taguchi method and Axiomatic Design in that a robust design is induced. However, different characteristics are found as well. The Taguchi method does not have the design range, and the probability of success may not be enough to express robustness. Our purpose is to find the one that has the highest probability of success and the smallest variation. A new index is proposed to satisfy these conditions. The index is defined by multiplication of the robustness weight function and the probability density function. The robustness weight function has the maximum at the target value and zero at the boundary of the design range. The validity of the index is proved through various examples.gh various examples.

• 한국지진공학회논문집
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• 제9권5호
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• pp.41-52
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• 2005

지진응답제어를 위한 효율적 방법으로 제시된 퍼지관리제어기법은 퍼지에 기반한 의사결정과정을 통하여 가변 제어이득행렬을 구현함으로써 하나의 제어이득만으로 표현되는 선형제어기법보다 개선된 제어성능을 발휘할 수 있다. 이 논문에서는 퍼지관리제어기법의 효율성을 하중 및 교량모델의 불확실성에 대한 제어성능의 강인성 측면에서 평가하였다. 강인성 평가에 있어서는 Dyke등이 제시한 벤치마크 교량에 대하여, 최적설계된 LQG기법과 제어성능을 비교하는 방법을 사용하였다. 불확실성을 주는 요인으로는 주파수 특성이 다른 여러 지진가속도의 규모 및 교량의 강성변화를 가정하였다. 최적설계된 LQG 제어기와 제어효과를 비교한 결과, FSC시스템이 지진의 종류와 규모에 따라 보다 작은 전력을 사용하면서도 개선된 제어성능을 발휘하였다. 특히, LQG 제어시스템이 강성변화에 대하여 불안정한 제어성능을 보인 반면, FSC 시스템은 매우 안정적인 응답제어효과를 보이면서도 제어시스템에 소요되는 전력량과 제어장치의 스트로크에 있어서도 큰 변화를 보이지 않음으로써 매우 탁월한 강인성을 보장할 수 있는 것으로 나타났다.

• 한국음향학회지
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• 제22권2호
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• pp.121-128
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• 2003

원거리 회의 시스템이나 차량 내 핸즈프리 통화에서 이용되는 음향 반향제거 시스템은 근단화자의 통화 상태에 대한 정보제공을 위해 동시통화검출기 (DTD: Double Talk Detector)를 포함한다. 이러한 동시 통화검출기는 주변 음향환경에 민감하게 작용하여 근단화자의 통화상태에 대해 잘못된 정보를 제공하기도 하는데, 본 논문에서는 이러한 기존의 문제점을 해결하여 보다 신뢰성 있는 음향 반향제어 시스템을 구축할 수 있는 새로운 동시통화 검출 알고리즘을 제안한다. 본 논문에서 제안된 음향 반향 제거 시스템은 지연없는 (Delayless) 서브밴드 적응 필터를 이용한 음향반향 제거기와 협대역 동시통화 검출기로 구성된다. 지연없는 서브밴드 적응음향 반향 알고리즘은 적은 계산량과 높은 수렴속도를 가지며 기존의 서브밴드(Subband) 적응음향 반향 제거기에서 문제가 되었던 지연 문제를 해결하는 등 음향 반향 제거 성능이 뛰어난 것으로 알려져 있다. 한편 본 논문에서 제안된 협대역 동시통화 검출기는 협대역 서브밴드 내에서 동시통화 검출 동작을 수행함으로서 다운 샘플링 (down-sampling)으로 인한 계산량 감소와 최저 주파수 서브밴드 대역의 저주파 신호 특성으로 인해 보다 신뢰성 있는 통화상태 정보를 제공할 수 있는 장점을 가진다. 본 연구에서 제안된 협대역 동시통화 검출 알고리즘의 성능은 광대역 동시통화 검출 알고리즘과 다양한 비교 시뮬레이션을 통해 그 성능을 입증하도록 한다.

• International Journal of Computer Science & Network Security
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• 제22권7호
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• pp.91-102
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• 2022

With the evolution of wireless sensor network (WSN) technology, the routing policy has foremost importance in the Internet of Things (IoT). A systematic routing policy is one of the primary mechanics to make certain the precise and robust transmission of wireless sensor networks in an energy-efficient manner. In an IoT environment, WSN is utilized for controlling services concerning data like, data gathering, sensing and transmission. With the advantages of IoT potentialities, the traditional routing in a WSN are augmented with decision-making in an energy efficient manner to concur finer optimization. In this paper, we study how to combine IoT-based deep learning classifier with routing called, Kriging Regressive Deep Belief Neural Learning (KR-DBNL) to propose an efficient data packet routing to cope with scalability issues and therefore ensure robust data packet transmission. The KR-DBNL method includes four layers, namely input layer, two hidden layers and one output layer for performing data transmission between source and destination sensor node. Initially, the KR-DBNL method acquires the patient data from different location. Followed by which, the input layer transmits sensor nodes to first hidden layer where analysis of energy consumption, bandwidth consumption and light intensity are made using kriging regression function to perform classification. According to classified results, sensor nodes are classified into higher performance and lower performance sensor nodes. The higher performance sensor nodes are then transmitted to second hidden layer. Here high performance sensor nodes neighbouring sensor with higher signal strength and frequency are selected and sent to the output layer where the actual data packet transmission is performed. Experimental evaluation is carried out on factors such as energy consumption, packet delivery ratio, packet loss rate and end-to-end delay with respect to number of patient data packets and sensor nodes.

• 한국생산제조학회지
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• 제19권1호
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• pp.145-155
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• 2010

This paper presents a new approach to obstacle avoidance for mobile robot in unknown or partially unknown environments. The method combines two navigation subsystems: low level and high level. The low level subsystem takes part in the control of linear, angular velocities using a multivariable PI controller, and the nonlinear position control. The high level subsystem uses ultrasonic and IR sensors to detect the unknown obstacle include static and dynamic obstacle. This approach provides both obstacle avoidance and target-following behaviors and uses only the local information for decision making for the next action. Also, we propose a new algorithm for the identification and solution of the local minima situation during the robot's traversal using the set of fuzzy rules. The system has been successfully demonstrated by simulations and experiments.

• International Journal of Quality Innovation
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• 제6권1호
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• pp.109-118
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• 2005

The parameter design is the most emphasized measure by researchers for a new products development. It is critical for makers to achieve simultaneously in both the time-to-market production and the quality enhancement. However, there are difficulties in practical application, such as (1) complexity and nonlinear relationships co-existed among the system's inputs, outputs and control parameters, (2) interactions occurred among parameters, (3) where the adjustment factors of Taguchi's two-phase optimization procedure cannot be sure to exist in practice, and (4) for some reasons, the data became lost or were never available. For these incomplete data, the Taguchi methods cannot treat them well. Neural networks have a learning capability of fault tolerance and model free characteristics. These characteristics support the neural networks as a competitive tool in processing multivariable input-output implementation. The successful fields include diagnostics, robotics, scheduling, decision-making, prediction, etc. This research is a case study of spherical annealing model. In the beginning, an original model is used to pre-fix a model of parameter design. Then neural networks are introduced to achieve another model. Study results showed both of them could perform the highest spherical level of quality.