• 제목/요약/키워드: Multi Series

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Temporal Fusion Transformers와 심층 학습 방법을 사용한 다층 수평 시계열 데이터 분석 (Temporal Fusion Transformers and Deep Learning Methods for Multi-Horizon Time Series Forecasting)

  • 김인경;김대희;이재구
    • 정보처리학회논문지:소프트웨어 및 데이터공학
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    • 제11권2호
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    • pp.81-86
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    • 2022
  • 시계열 데이터는 주식, IoT, 공장 자동화와 같은 다양한 실생활에서 수집되고 활용되고 있으며, 정확한 시계열 예측은 해당 분야에서 운영 효율성을 높일 수 있어서 전통적으로 중요한 연구 주제이다. 전반적인 시계열 데이터의 향상된 특징을 추출할 수 있는 대표적인 시계열 데이터 분석 방법인 다층 수평 예측은 최근 부가적 정보를 포함하는 시계열 데이터에 내재한 이질성(heterogeneity)까지 포괄적으로 분석에 활용하여 향상된 시계열 예측한다. 하지만 대부분의 심층 학습 기반 시계열 분석 모델들은 시계열 데이터의 이질성을 반영하지 못했다. 따라서 우리는 잘 알려진 temporal fusion transformers 방법을 사용하여 실생활과 밀접한 실제 데이터를 이질성을 고려한 다층 수평 예측에 적용하였다. 결과적으로 주식, 미세먼지, 전기 소비량과 같은 실생활 시계열 데이터에 적용한 방법이 기존 예측 모델보다 향상된 정확도를 가짐을 확인할 수 있었다.

다중속성 시계열 데이타베이스의 효율적인 유사 검색 (Efficient Similarity Search in Multi-attribute Time Series Databases)

  • 이상준
    • 정보처리학회논문지D
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    • 제14D권7호
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    • pp.727-732
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    • 2007
  • 시계열에 대한 색인 및 검색 연구는 하나의 속성으로 구성된 시계열에 대하여 주로 수행되어 왔다. 그러나 음악, 비디오 등의 멀티미디어 데이타베이스는 다중속성 시계열 데이타베이스에서 유사 검색을 다룰 수 있어야 한다. 기존의 다중속성 시계열 데이타베이스에 대한 연구는 두 다중속성 시퀀스간의 유사도로 속성 간의 거리의 누적을 사용하고 있기에, 개별적인 속성 시퀀스에 대한 정보를 상실하게 된다. 본 연구에서는 이러한 문제를 해결하기 위해 속성 시퀀스 측면에서 다중속성 시계열 데이타베이스의 유사검색 기법을 제안한다. 제안된 기법은 검색 공간을 효율적으로 줄일 수 있으며, 착오 누락이 없음을 보장한다. 또한 실험을 통해 제안된 기법의 성능 향상을 확인하였다.

MRAS Based Sensorless Control of a Series-Connected Five-Phase Two-Motor Drive System

  • Khan, M. Rizwan;Iqbal, Atif
    • Journal of Electrical Engineering and Technology
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    • 제3권2호
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    • pp.224-234
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    • 2008
  • Multi-phase machines can be used in variable speed drives. Their applications include electric ship propulsion, 'more-electric aircraft' and traction applications, electric vehicles, and hybrid electric vehicles. Multi-phase machines enable independent control of a few numbers of machines that are connected in series in a particular manner with their supply being fed from a single voltage source inverter(VSI). The idea was first implemented for a five-phase series-connected two-motor drive system, but is now applicable to any number of phases more than or equal to five-phase. The number of series-connected machines is a function of the phase number of VSI. Theoretical and simulation studies have already been reported for number of multi-phase multi-motor drive configurations of series-connection type. Variable speed induction motor drives without mechanical speed sensors at the motor shaft have the attractions of low cost and high reliability. To replace the sensor, information concerning the rotor speed is extracted from measured stator currents and voltages at motor terminals. Open-loop estimators or closed-loop observers are used for this purpose. They differ with respect to accuracy, robustness, and sensitivity against model parameter variations. This paper analyses operation of an MRAS estimator based sensorless control of a vector controlled series-connected two-motor five-phase drive system with current control in the stationary reference frame. Results, obtained with fixed-voltage, fixed-frequency supply, and hysteresis current control are presented for various operating conditions on the basis of simulation results. The purpose of this paper is to report the first ever simulation results on a sensorless control of a five-phase two-motor series-connected drive system. The operating principle is given followed by a description of the sensorless technique.

초단기 및 단기 다변수 시계열 결합모델을 이용한 24시간 부하예측 (24 hour Load Forecasting using Combined Very-short-term and Short-term Multi-Variable Time-Series Model)

  • 이원준;이문수;강병오;정재성
    • 전기학회논문지
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    • 제66권3호
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    • pp.493-499
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    • 2017
  • This paper proposes a combined very-short-term and short-term multi-variate time-series model for 24 hour load forecasting. First, the best model for very-short-term and short-term load forecasting is selected by considering the least error value, and then they are combined by the optimal forecasting time. The actual load data of industry complex is used to show the effectiveness of the proposed model. As a result the load forecasting accuracy of the combined model has increased more than a single model for 24 hour load forecasting.

EMI based multi-bolt looseness detection using series/parallel multi-sensing technique

  • Chen, Dongdong;Huo, Linsheng;Song, Gangbing
    • Smart Structures and Systems
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    • 제25권4호
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    • pp.423-432
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    • 2020
  • In this paper, a novel but practical approach named series/parallel multi-sensing technique was proposed to evaluate the bolt looseness in a bolt group. The smart washers (SWs), which were fabricated by embedding a Lead Zirconate Titanate (PZT) transducer into two flat metal rings, were installed to the bolts group. By series connection of SWs, the impedance signals of different bolts can be obtained through only one sweep. Therefore, once the loosening occurred, the shift of different peak frequencies can be used to locate which bolt has loosened. The proposed multi input single output (MISO) damage detection scheme is very suitable for the structural health monitoring (SHM) of joint with a large number of bolts connection. Another notable contribution of this paper is the proposal of 3-dB bandwidth root mean square deviation (3 dB-RMSD) which can quantitatively evaluate the severity of bolt looseness. Compared with the traditional naked-eye observation method, the equivalent circuit based 3-dB bandwidth can accurately define the calculation range of RMSD. An experiment with three bolted connection specimens that installed the SWs was carried out to validate our proposed approach. Experimental result shows that the proposed 3 dB-RMSD based multi-sensing technique can not only identify the loosened bolt but also monitor the severity of bolt looseness.

Time-Series Forecasting Based on Multi-Layer Attention Architecture

  • Na Wang;Xianglian Zhao
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제18권1호
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    • pp.1-14
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    • 2024
  • Time-series forecasting is extensively used in the actual world. Recent research has shown that Transformers with a self-attention mechanism at their core exhibit better performance when dealing with such problems. However, most of the existing Transformer models used for time series prediction use the traditional encoder-decoder architecture, which is complex and leads to low model processing efficiency, thus limiting the ability to mine deep time dependencies by increasing model depth. Secondly, the secondary computational complexity of the self-attention mechanism also increases computational overhead and reduces processing efficiency. To address these issues, the paper designs an efficient multi-layer attention-based time-series forecasting model. This model has the following characteristics: (i) It abandons the traditional encoder-decoder based Transformer architecture and constructs a time series prediction model based on multi-layer attention mechanism, improving the model's ability to mine deep time dependencies. (ii) A cross attention module based on cross attention mechanism was designed to enhance information exchange between historical and predictive sequences. (iii) Applying a recently proposed sparse attention mechanism to our model reduces computational overhead and improves processing efficiency. Experiments on multiple datasets have shown that our model can significantly increase the performance of current advanced Transformer methods in time series forecasting, including LogTrans, Reformer, and Informer.

A Multi-step Time Series Forecasting Model for Mid-to-Long Term Agricultural Price Prediction

  • Jonghyun, Park;Yeong-Woo, Lim;Do Hyun, Lim;Yunsung, Choi;Hyunchul, Ahn
    • 한국컴퓨터정보학회논문지
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    • 제28권2호
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    • pp.201-207
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    • 2023
  • 본 논문에서는 Multi-Step Time Series의 세 가지 전략을 비교 분석하기 위해 LGBM, MLP, LSTM, GRU를 사용하여 농산물 중장기 가격 예측에 대한 최적의 모형을 제안한다. 제안 모형은 다각도로 전략을 선택하여 모델과 전략간 최적의 조합을 찾도록 설계되었다. 기존 농산물 가격 예측 연구에서는 전통 계량경제 모델인 ARIMA를 비롯하여 LSTM 계열 모델이 주로 사용된 반면 Multi-Step Time Series 관련 농산물 가격 예측 연구는 매우 제한적이다. 본 연구에서는 농산물 가격의 변동성 정도에 따라 두 개의 기간으로 나누어 실험을 진행하였으며, Direct, Hybrid, Multiple Outputs 등 세 전략의 중장기 가격 예측 결과 Hybrid 접근법이 상대적으로 우수한 성능을 보였다.본 연구 결과는 중장기 일별 가격 예측을 고도화할 수 있는 효과적인 대안을 제시한다는 측면에서 학술적, 실무적 의의를 갖는다.

Time-Discretization of Nonlinear Systems with Delayed Multi-Input Using Taylor Series

  • Park, Ji-Hyang;Chong, Kil-To;Nikolaos Kazantzis;Alexander G. Parlos
    • Journal of Mechanical Science and Technology
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    • 제18권7호
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    • pp.1107-1120
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    • 2004
  • This study proposes a new scheme for the sampled-data representation of nonlinear systems with time-delayed multi-input. The proposed scheme is based on the Taylor-series expansion and zero-order hold assumption. The mathematical structure of a new discretization scheme is explored. On the basis of this structure, the sampled-data representation of nonlinear systems including time-delay is derived. The new scheme is applied to nonlinear systems with two inputs and then the delayed multi-input general equation is derived. The resulting time-discretization provides a finite-dimensional representation of nonlinear control systems with time-delay enabling existing controller design techniques to be applied to them. In order to evaluate the tracking performance of the proposed scheme, an algorithm is tested for some of the examples including maneuvering of an automobile and a 2-DOF mechanical system.

직렬 연결된 GTO로 구성된 멀티레벨 인버터에 적합한 새로운 회생 스너버에 관한 연구 (A Novel Regenerative Snubber suitable to Multi-Level Inverters with Series-Connected GTOs)

  • 채균;조국춘;정구호;류태하;조규형
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1996년도 하계학술대회 논문집 A
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    • pp.585-587
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    • 1996
  • A simple regenerative snubber structure is proposed, which is applicable to multi-level inverter with series-connected GTOs for high power applications. The novel snubber structure can solve large energy loss problems and guarantee safe operation of power converter can be achieved. The proposed new snubber has the potential of high performance and high reliability and is particularly suitable to high power and multi-level application with series connected power devices. The snubber voltage and current waveforms are analized and shown the simulation and experimental results for a GTO 3-level inverter circuit with inductive load.

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Discretization of Nonlinear Systems with Delayed Multi-Input VIa Taylor Series and Scaling and Squaring Technique

  • Yuanliang Zhang;Chong Kil To
    • Journal of Mechanical Science and Technology
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    • 제19권11호
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    • pp.1975-1987
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    • 2005
  • An input time delay always exists in practical systems. Analysis of the delay phenomenon in a continuous-time domain is sophisticated. It is appropriate to obtain its corresponding discrete-time model for implementation via digital computers. In this paper a new scheme for the discretization of nonlinear systems using Taylor series expansion and the zero-order hold assumption is proposed. The mathematical structure of the new discretization method is analyzed. On the basis of this structure the sampled-data representation of nonlinear systems with time-delayed multi-input is presented. The delayed multi-input general equation has been derived. In particular, the effect of the time-discretization method on key properties of nonlinear control systems, such as equilibrium properties and asymptotic stability, is examined. Additionally, hybrid discretization schemes that result from a combination of the scaling and squaring technique (SST) with the Taylor series expansion are also proposed, especially under conditions of very low sampling rates. Practical issues associated with the selection of the method's parameters to meet CPU time and accuracy requirements, are examined as well. A performance of the proposed method is evaluated using a nonlinear system with time delay maneuvering an automobile.