• Title/Summary/Keyword: Sequential convergence

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A Sequential Approximate Optimization Technique Using the Previous Response Values (응답량 재사용을 통한 순차 근사최적설계)

  • Hwang Tae-Kyung;Choi Eun-Ho;Lim O-Kaung
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.29 no.1 s.232
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    • pp.45-52
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    • 2005
  • A general approximate optimization technique by sequential design domain(SDD) did not save response values for getting an approximate function in each step. It has a disadvantage at aspect of an expense. In this paper, previous response values are recycled for constructing an approximate function. For this reason, approximation function is more accurate. Accordingly, even if we did not determine move limit, a system is converged to the optimal design. Size and shape optimization using approximate optimization technique is carried out with SDD. Algorithm executing Pro/Engineer and ANSYS are automatically adopted in the approximate optimization program by SDD. Convergence criterion is defined such that optimal point must be located within SDD during the three steps. The PLBA(Pshenichny-Lim-Belegundu-Arora) algorithm is used to solve approximate optimization problems. This algorithm uses the second-order information in the direction finding problem and uses the active set strategy.

A Sequential Orientation Kalman Filter for AHRS Limiting Effects of Magnetic Disturbance to Heading Estimation

  • Lee, Jung Keun;Choi, Mi Jin
    • Journal of Electrical Engineering and Technology
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    • v.12 no.4
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    • pp.1675-1682
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    • 2017
  • This paper deals with three dimensional orientation estimation algorithm for an attitude and heading reference system (AHRS) based on nine-axis inertial/magnetic sensor signals. In terms of the orientation estimation based on the use of a Kalman filter (KF), the quaternion is arguably the most popular orientation representation. However, one critical drawback in the quaternion representation is that undesirable magnetic disturbances affect not only yaw estimation but also roll and pitch estimations. In this paper, a sequential direction cosine matrix-based orientation KF for AHRS has been presented. The proposed algorithm uses two linear KFs, consisting of an attitude KF followed by a heading KF. In the latter, the direction of the local magnetic field vector is projected onto the heading axis of the inertial frame by considering the dip angle, which can be determined after the attitude KF. Owing to the sequential KF structure, the effects of even extreme magnetic disturbances are limited to the roll and pitch estimations, without any additional decoupling process. This overcomes an inherent issue in quaternion-based estimation algorithms. Validation test results show that the proposed method outperforms other comparison methods in terms of the yaw estimation accuracy during perturbations and in terms of the recovery speed.

Global Optimization Using a Sequential Algorithm with Orthogonal Arrays in Discrete Space (이산공간에서 순차적 알고리듬(SOA)을 이용한 전역최적화)

  • Cho Bum-Sang;Yi Jeong-Wook;Park Gyung-Jin
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.29 no.10 s.241
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    • pp.1369-1376
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    • 2005
  • In structural design, the design variables are frequently selected from certain discrete values. Various optimization algorithms have been developed fDr discrete design. It is well known that many function evaluations are needed in such optimization. Recently, sequential algorithm with orthogonal arrays (SOA), which is a search algorithm for a local minimum in a discrete space, has been developed. It considerably reduces the number of function evaluations. However, it only finds a local minimum and the final solution depends on the initial values of the design variables. A new algorithm is proposed to adopt a genetic algorithm (GA) in SOA. The GA can find a solution in a global sense. The solution from the GA is used as the initial design of SOA. A sequential usage of the GA and SOA is carried out in an iterative manner until the convergence criteria are satisfied. The performance of the algorithm is evaluated by various examples.

Batch Time Interval and Initial State Estimation using GMM-TS for Target Motion Analysis (GMM-TS를 이용한 표적기동분석용 배치구간 및 초기상태 추정 기법)

  • Kim, Woo-Chan;Song, Taek-Lyul
    • Journal of Institute of Control, Robotics and Systems
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    • v.18 no.3
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    • pp.285-294
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    • 2012
  • Using bearing measurement only, target motion state is not directly obtained so that TMA (Target Motion Analysis) is needed for this situation. TMA is a nonlinear estimation technique used in passive SONAR systems. Also it is the one of important techniques for underwater combat management systems. TMA can be divided to two parts: batch estimation and sequential estimation. It is preferable to use sequential estimation for reducing computational load as well as adaptively to target maneuvers, batch estimation is still required to attain target initial state vector for convergence of sequential estimation. Selection of batch time interval which depends on observability is critical in TMA performance. Batch estimation in general utilizes predetermined batch time interval. In this paper, we propose a new method called the BTIS (Batch Time Interval and Initial State Estimation). The proposed BTIS estimates target initial status and determines the batch time interval sequentially by using a bank of GMM-TS (Gaussian Mixture Measurement-Track Splitting) filters. The performance of the proposal method is verified by a Monte Carlo simulation study.

Deep Learning Framework with Convolutional Sequential Semantic Embedding for Mining High-Utility Itemsets and Top-N Recommendations

  • Siva S;Shilpa Chaudhari
    • Journal of information and communication convergence engineering
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    • v.22 no.1
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    • pp.44-55
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    • 2024
  • High-utility itemset mining (HUIM) is a dominant technology that enables enterprises to make real-time decisions, including supply chain management, customer segmentation, and business analytics. However, classical support value-driven Apriori solutions are confined and unable to meet real-time enterprise demands, especially for large amounts of input data. This study introduces a groundbreaking model for top-N high utility itemset mining in real-time enterprise applications. Unlike traditional Apriori-based solutions, the proposed convolutional sequential embedding metrics-driven cosine-similarity-based multilayer perception learning model leverages global and contextual features, including semantic attributes, for enhanced top-N recommendations over sequential transactions. The MATLAB-based simulations of the model on diverse datasets, demonstrated an impressive precision (0.5632), mean absolute error (MAE) (0.7610), hit rate (HR)@K (0.5720), and normalized discounted cumulative gain (NDCG)@K (0.4268). The average MAE across different datasets and latent dimensions was 0.608. Additionally, the model achieved remarkable cumulative accuracy and precision of 97.94% and 97.04% in performance, respectively, surpassing existing state-of-the-art models. This affirms the robustness and effectiveness of the proposed model in real-time enterprise scenarios.

Shape Optimization for Reinforced Concrete Culvert (철근콘크리트 암거의 형상 최적화)

  • Kim, Kee-Dae
    • Journal of the Korean Society of Industry Convergence
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    • v.5 no.3
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    • pp.261-268
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    • 2002
  • In this paper, the shape optimization is considered over the upper slab of reinforced concrete culvert. The sequential linear programming method (SLP) is used as a rational approach to this shape optimization. To make a comparison between the arch shaped member and the straight member for the upper slab, the culverts with 5~20m earth height were adopted. It is shown that the optimum rise/span is about 7%-13%, and the arch shaped member is more cheap (over 10%) than the straight member for the construction cost.

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Development of ICT as an evolutionary process

  • Hwang, Gyu-hee
    • Journal of Korea Technology Innovation Society
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    • v.5 no.2
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    • pp.189-211
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    • 2002
  • The research shows how the technological change of 'Information and Communication Technology' (ICT) is accompanied with the usage change. It aims to provide a better conceptualization with empirical findings about the fact that the technological development of ICT is a convergence process of ICT factors with the usage of ICT moving from a limited coverage toward a general-purpose. The research adapts a descriptive methodology on a historical matter and demonstrates how it can be conducted through analytical description of Input-Output tables (I/O) the over periods. The case is about the UK with sequential I/O during 1970s- 90s.

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Optimum Design of Retaining Wall with Seismic Constraints (내진제약조건(耐震制約條件)을 갖는 옹벽(擁壁)의 최적설계(最適設計))

  • Kim, Kee-Dae
    • Journal of the Korean Society of Industry Convergence
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    • v.6 no.2
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    • pp.95-102
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    • 2003
  • In this paper, optimum design is considered over the retaining wall with seismic constraints. The sequential linear programming method(SLP) is used as a rational approach to this optimum design. To make a comparison between the seismic design and the normal design, retaining wall with 4~7m height were adopted. It is shown that the seismic design is more expensive (over 30%) than the normal design for the construction cost.

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A Study on the Composition of Smart Home Patterns through Association Analysis and Sequential Analysis (연관분석과 순차분석을 통한 스마트홈 패턴 구성 방안)

  • Seung-Min Jeoing;Han-Eol Choi;Gyeong-Ho Gwag;Min-Jae Kim;Hae-Rin Jeong
    • Proceedings of the Korea Information Processing Society Conference
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    • 2023.11a
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    • pp.376-377
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    • 2023
  • 스마트홈은 기술 시스템, 자동화 프로세스, 원격 제어 기기 등을 아파트나 주택에서 사용하는 것을 말한다. 주요 목적은 가정에서 삶의 질과 편의성을 높이는 것이다. 현재의 스마트홈은 사용자의 원격 제어 방식을 사용하고 있다. 이러한 방식은 고정된 시간에만 스마트홈이 작동하도록 한다는 문제가 있었다. 연관분석과 순차분석을 통해 AI가 상황과 사용자의 취향을 학습한다면, 스스로 최적화된 패턴을 제공할 수 있을 것이다.

Opto-Digital Implementation of Convergence-Controlled Stereo Target Tracking System (주시각이 제어된 스테레오 물체추적 시스템의 광-디지털적 구현)

  • 고정환;이재수;김은수
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.27 no.4B
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    • pp.353-364
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    • 2002
  • In this paper, a new onto-digital stereo object-tracking system using hierarchical digital algorithms and optical BPEJTC is proposed. This proposed system can adaptively track a moving target by controlling the convergence of stereo camera. firstly, the target is detected through the background matching of the sequential input images by using optical BPEJTC and then the target area is segmented by using the target projection mask which is composed by hierarchical digital processing of image subtraction, logical operation and morphological filtering. Secondly, the location's coordinate of the moving target object for each of the sequential input frames can be extracted through carrying out optical BPEJTC between the reference image of the target region mask and the stereo input image. Finally, the convergence and pan/tilt of stereo camera can be sequentially controlled by using these target coordinate values and the target can be kept in tracking. Also, a possibility of real-time implementation of the adaptive stereo object tracking system is suggested through optically implementing the proposed target extraction and convergence control algorithms.