• Nuclear Engineering and Technology
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• 제53권12호
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• pp.3944-3951
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• 2021

Several reasons such as no free lunch theorem indicate that there is not a universal Feature selection (FS) technique that outperforms other ones. Moreover, some approaches such as using synthetic dataset, in presence of large number of FS techniques, are very tedious and time consuming task. In this study to tackle the issue of dependency of estimation accuracy on the selected FS technique, a methodology based on the heterogeneous ensemble is proposed. The performance of the major learning algorithms of neural network (i.e. the FFNN-BR, the FFNN-LM) in combination with the diverse FS techniques (i.e. the NCA, the F-test, the Kendall's tau, the Pearson, the Spearman, and the Relief) and different combination techniques of the heterogeneous ensemble (i.e. the Min, the Median, the Arithmetic mean, and the Geometric mean) are considered. The target parameters/transients of Bushehr nuclear power plant (BNPP) are examined as the case study. The results show that the Min combination technique gives the more accurate estimation. Therefore, if the number of FS techniques is m and the number of learning algorithms is n, by the heterogeneous ensemble, the search space for acceptable estimation of the target parameters may be reduced from n × m to n × 1. The proposed methodology gives a simple and practical approach for more reliable and more accurate estimation of the target parameters compared to the methods such as the use of synthetic dataset or trial and error methods.

• Smart Structures and Systems
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• 제29권2호
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• pp.337-350
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• 2022

This paper focuses on predicting the post-heating mechanical properties of cementitious composites reinforced with multi-scale additives using the Artificial Neural Network (ANN) approach. A total of four different feed-forward ANN models are developed using 261 data sets collected from 18 published sources. The models are optimized using 12 input parameters selected based on a comprehensive literature review to predict the residual compressive strength, the residual flexural strengths, elastic modulus, and fracture energy of heat-damaged cementitious specimens. Furthermore, the ANN is employed to predict the impact of several variables including; the content of polypropylene (PP) microfibers and carbon nanotubes (CNTs) used in the concrete, mortar, or paste mix design, length of PP fibers, the average diameter of CNTs, and the average length of CNTs. The influence of the studied parameters is investigated at different heating levels ranged from 25℃ to 800℃. The results demonstrate that the developed ANN models have a strong potential for predicting the mechanical properties of the heated cementitious composites based on the mixing ingredients in addition to the heating conditions.

• Korean Chemical Engineering Research
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• 제61권2호
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• pp.328-339
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• 2023

Methanol steam reforming (MSR) is a promising method for hydrogen supplying as a critical step in hydrogen fuel cell commercialization in mobile applications. Modelling and understanding of the reactor behavior is an attractive research field to develop an efficient reformer. Three-layer feed-forward artificial neural network (ANN) and Box-Behnken design (BBD) were used to modelling of MSR process using the Cu-SiO₂ aerogel catalyst. Furthermore, impacts of the basic operational variables and their mutual interactions were studied. The results showed that the most affecting parameters were the reaction temperature (56%) and its quadratic term (20.5%). In addition, it was also found that the interaction between temperature and Steam/Methanol ratio is important on the MSR performance. These models precisely predict MSR performance and have great agreement with experimental results. However, on the basis of statistical criteria the ANN technique showed the greater modelling ability as compared with statistical BBD approach.

• 국제학술발표논문집
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• The 6th International Conference on Construction Engineering and Project Management
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• pp.195-199
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• 2015

Many conventional management methods have emphasized the minimization of required resources along the supply chain. Accordingly, this paper presents a proposed method called the Virtual Design and Construction (VDC)-aided system. It is based on object-oriented resource control, in order to accomplish a feed-forward control monitoring supply chain logistics. The system is supported by two main parts: (1) IT-based Technologies; and (2) VDC Models. They enable the system to convey proactive information from the detection technology to its linked visualization. The paper includes a field study as the system's pre-test: the Scaffolding Works in a LNG Mega Project. The study demonstrates a system of real-time productivity monitoring by use of the RFIDbased Mobile Information Hub. The on-line 'productivity dashboard' provides an opportunity to display the continuing processes for each work-package. This research project offers the observed opportunities created by the developed system. Future work will entail research experiments aimed towards system validation.

• 드라이브 ㆍ 컨트롤
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• 제21권1호
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• pp.31-37
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• 2024

In this study, to prevent accidents in underground facilities during excavation, we developed a Lv.3 automated control system that can be configured as an electronic control system without changing the existing hydraulic system in a general excavator and utilized digital map information of underground facilities. We aimed to develop a strategy to prevent accidents caused by operator error. To implement this, a real-time excavator bucket end position recognition and control system was developed through angle measurement of the boom, arm, and bucket using an electronic joystick, RTK-GPS, and angle sensors. In addition, excavators are large, machine-based equipment, and it is difficult to control overshoot due to inertia with feedback control using position recognition information of the bucket tip. Therefore, feed-forward control is used to calculate the moving speed of the bucket tip in real-time to determine the target position. We developed a technology that can converge and verified the performance of the developed system through actual vehicle installation and field tests.

• Journal of Information Technology Applications and Management
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• 제30권3호
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• pp.1-13
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• 2023

Demand forecasting is a crucial task for an online retail where has to manage daily fresh foods effectively. Failing in forecasting results loss of profitability because of incompetent inventory management. This study investigated the optimal performance of different forecasting models for a very short shelf-life product. Demand data of 13 perishable items with aging of 210 days were used for analysis. Our comparison results of four methods: Trivial Identity, Seasonal Naïve, Feed-Forward and Autoregressive Recurrent Neural Networks (DeepAR) reveals that DeepAR outperforms with the lowest MAPE. This study also suggests the managerial implications by employing coefficient of variation (CV) as demand variation indicators. Three classes: Low, Medium and High variation are introduced for classify 13 products into groups. Our analysis found that DeepAR is suitable for medium and high variations, while the low group can use any methods. With this approach, the case can gain benefit of better fill-rate performance.

• 한국가스학회지
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• 제18권1호
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• pp.46-51
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• 2014

이 논문의 목적은 자동차 램프의 초음파 접합 공정을 합성한 자동차 램프 생산시스템에 관한 연구이다. 램프어셈블리를 생산할 때 독립된 단순 공정에 의해 사출과 초음파 접합, 항온풀림, 조립과 포장을 하던 분리된 작업공정을 원스텝(One-step) 일관공정으로 합성하여 초음파 접합시 발생되는 미세한 발생가스와 소음에 대하여 작업자에게 미치는 영향을 최소화하였다. 또한, 합성 공정에 의한 에너지 저감과 이를 자동공정에 의해 생산함으로써 생산 효율을 극대화하였다. 이 방식은 제어시스템의 타당성을 검토하기 위해 수학적 모델링을 하였고, 이들 수식을 이용하여 플랜트의 전달함수와 필요에 따라 bode선도를 이용하여 안정성과 적합한 제어기를 선정하였다. 이 연구에서 사출 물을 뒤집기 위한 $180^{\circ}$ 회전 제어장치는 중력의 영향으로 비선형 항 $M_{eq}\;lcos{\theta}(t)$이 나타났고, 이를 해결하기위해 피드포워드 제어기법을 적용하여 시스템의 선형화 및 안정화를 확보하였다.

• 한국통신학회논문지
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• 제24권12A호
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• pp.2015-2024
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• 1999

디지털 통신 시스템의 기저대역 신호처리를 효율적으로 구현하기 위한 새로운 복소수 필터구조를 제안하고, 이를 적용하여 채널등화용 적응 결정귀환 등화기 (Adaptive Decision-Feedback Equalizer; ADFE) 칩셋을 설계하였다. 새로운 복소수 필터구조는 기존의 2의 보수 대신에 redundant binary (RB) 수치계를 적용한 효율적인 복소수 승산 및 누적연산을 바탕으로 한다. 제안된 방법을 적용하면, N-탭 복소수 필터는 2N개의 RB 승산기와 2N-2개의 RB 가산기로 구현되며, 필터 탭 당 Tm,RB＋Ta,RB (단, Tm,RB, Ta,RB는 각각 RB 승산기 및 가산기의 지해 고속동작이 가능하다. 제안된 방법을 적용하여 설계된 ADFE는 FFEM (Feed-Foreward Equalizer Module)과 DFEM (Decision-Feedback Equalizer Module)로 구성되며, 필요에 따라 필터 탭을 확장할 수 있도록 설계되었다. 2-탭 복소수 필터, LMS 계수갱신 회로 및 부가회로 등으로 구성되는 각 모듈은 COSSAP과 VHDL을 이용한 모델링 및 검증과정을 거쳐 0.8-㎛ SOG (Sea-Of-Gate) 셀 라이브러리를 사용하여 논리합성 되었으며, 26,000여개의 게이트로 구성된다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2003년도 ICCAS
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• pp.1489-1494
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• 2003

A neuromuscular control system of a myoelectric prosthetic hand (PH) constitutes a nonlinear system with a dead zone whose magnitude is equal to its joint angle when the PH just grasps an object. This is because the neuromuscular control system remains an open-loop system until the PH grasps the object but it constitutes a feedback control system after the PH griped the object in which a torque induced in the fingers of the PH is fed back. To improve the transient performance of the control system, it is desirable to make the feed-forward gain as large as possible, so long as the stability of the system is not impaired. It is also desired that the control system remains stable even when the PH lifts a heavy or rigid object, because this makes the closed loop gain large and leads to the closed system unstable. According to the theory of stability analysis of nonlinear systems, we can only know the sufficient conditions that the system should be stable. Thus the nonlinear theory on stability is insufficient to be used to design the neuromuscular control system for improving its transient responses. This paper shows that the nonlinear system with a dead zone can be approximated to a linear feedback system and that well-known methods of analysis and design on linear control systems can be applicable. It is also shown through various simulation results that errors induced by approximation are practically negligible and thus the design methods are quite accurate.

• International Journal of Control, Automation, and Systems
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• 제5권6호
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• pp.643-651
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• 2007

The various blood pressure simulators have been proposed to evaluate and improve the performance of the automatic sphygmomanometer. These have some problems such as the deviation of the actual blood pressure waveform, limitation in the blood pressure condition of the simulator, or difficulty in displaying the blood flow. An improved simulator using disturbance observer is proposed to supplement the current problems of the blood pressure simulator. The proposed simulator has an artificial arm model capable of feeding appropriate fluids that can generate the blood pressure waveform to evaluate the automatic sphygmomanometer. A controller was designed and thereafter, simulation was performed to control the output signal with respect to the reference input in the fluid dynamic model using the proposed proportional control valve. To minimize the external fluctuation of pressure applied to the artificial arm, a disturbance observer was designed on the plant. A hybrid controller combined with a proportional controller and feed-forward controller was fabricated after applying a disturbance observer to the control plant. Comparison of the simulations between the conventional proportional controller and the proposed hybrid controller indicated that even though the former showed good control performance without disturbance, it was affected by the disturbance signal induced by the cuff. The latter exhibited an excellent performance under both situations.