• 제목/요약/키워드: Computational burden reduction

검색결과 46건 처리시간 0.028초

Optimal Voltage and Reactive Power Scheduling for Saving Electric Charges using Dynamic Programming with a Heuristic Search Approach

  • Jeong, Ki-Seok;Chung, Jong-Duk
    • Journal of Electrical Engineering and Technology
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    • 제11권2호
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    • pp.329-337
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    • 2016
  • With the increasing deployment of distributed generators in the distribution system, a very large search space is required when dynamic programming (DP) is applied for the optimized dispatch schedules of voltage and reactive power controllers such as on-load tap changers, distributed generators, and shunt capacitors. This study proposes a new optimal voltage and reactive power scheduling method based on dynamic programming with a heuristic searching space reduction approach to reduce the computational burden. This algorithm is designed to determine optimum dispatch schedules based on power system day-ahead scheduling, with new control objectives that consider the reduction of active power losses and maintain the receiving power factor. In this work, to reduce the computational burden, an advanced voltage sensitivity index (AVSI) is adopted to reduce the number of load-flow calculations by estimating bus voltages. Moreover, the accumulated switching operation number up to the current stage is applied prior to the load-flow calculation module. The computational burden can be greatly reduced by using dynamic programming. Case studies were conducted using the IEEE 30-bus test systems and the simulation results indicate that the proposed method is more effective in terms of saving electric charges and improving the voltage profile than loss minimization.

잔향 생성기에서 심리 음향 필터를 이용한 고속 컨벌루션 방법 (Fast Convolution Method using Psycho-acoustic Filters in Sound Reverberator)

  • 신민철;왕세명
    • 한국소음진동공학회:학술대회논문집
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    • 한국소음진동공학회 2007년도 추계학술대회논문집
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    • pp.1037-1041
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    • 2007
  • With the advent of sound field simulator, many sound fields have been reproduced by obtaining the impulse responses of specific acoustic spaces like famous concert hall, opera house. This sound field reproduction has been done by the linear convolution operation between the sound input signal and the impulse response of certain acoustic space. However, the conventional finite impulse response based linear convolution operation always makes real-time implementation of sound field generator impossible due to the large amount of computational burden. This paper introduces the fast convolution method using perceptual redundancy in the processed signals, input audio signal and room impulse response. Temporal and spectral psycho-acoustic filters considering masking effects are implemented in the proposed convolution structure. It reduces the computational burden of convolution methods for realtime implementation of a sound field generator. The conventional convolutions are compared with the proposed one in views of computational burden and sound quality. In the proposed method, a considerable reduction in the computational burden was realized with acceptable changes in sound quality.

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잔향 생성기에서 실시간 마스킹 효과를 이용한 고속 컨벌루션 방법 (Fast Convolution Method Using Real-time Masking Effects in Sound Reverberator)

  • 신민철;왕세명
    • 한국소음진동공학회논문집
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    • 제18권2호
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    • pp.231-237
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    • 2008
  • With the advent of sound field simulator, many sound fields have been reproduced by obtaining the impulse responses of specific acoustic spaces like famous concert hall, opera house. This sound field reproduction has been done by the linear convolution operation between the sound input signal and the impulse response of certain acoustic space. However, the conventional finite impulse response based linear convolution operation always makes real-time implementation of sound field generator impossible due to the large amount of computational burden. This paper introduces the fast convolution method using perceptual redundancy in the processed signals, input audio signal and room impulse response. Temporal and spectral real-time masking blocks are implemented in the proposed convolution structure. It reduces the computational burden of convolution methods for real-time implementation of a sound field generator. The conventional convolutions are compared with the proposed one in views of computational burden and sound quality. In the proposed method, a considerable reduction in the computational burden was realized with acceptable changes in sound quality.

Computational Reduction in Keyword Spotting System Based on the Bucket Box Intersection (BBI) Algorithm

  • Lee, Kyo-Heok;Kim, Hyung-Soon
    • The Journal of the Acoustical Society of Korea
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    • 제19권2E호
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    • pp.27-31
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    • 2000
  • Evaluating log-likelihood of Gaussian mixture density is major computational burden for the keyword spotting system using continuous HMM. In this paper, we employ the bucket box intersection (BBI) algorithm to reduce the computational complexity of keyword spotting. We make some modification in implementing BBI algorithm in order to increase the discrimination ability among the keyword models. According to our keyword spotting experiments, the modified BBI algorithm reduces 50% of log-likelihood computations without performance degradation, while the original BBI algorithm under the same condition reduces only 30% of log-likelihood computations.

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다관절 로봇의 계층적 제어를 위한 HQP의 연산 비용 감소 방법 (Computational Cost Reduction Method for HQP-based Hierarchical Controller for Articulated Robot)

  • 박민규;김동환;오용환;이이수
    • 로봇학회논문지
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    • 제17권1호
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    • pp.16-24
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    • 2022
  • This paper presents a method that can reduce the computational cost of the hierarchical quadratic programming (HQP)-based robot controller. Hierarchical controllers can effectively manage articulated robots with many degrees of freedom (DoFs) to perform multiple tasks. The HQP-based controller is one of the generic hierarchical controllers that can provide a control solution guaranteeing strict task priority while handling numerous equality and inequality constraints. However, according to a large amount of computation, it can be a burden to use it for real-time control. Therefore, for practical use of the HQP, we propose a method to reduce the computational cost by decreasing the size of the decision variable. The computation time and control performance of the proposed method are evaluated by real robot experiments with a 15 DoFs dual-arm manipulator.

Predictive Current Control for Multilevel Cascaded H-Bridge Inverters Based on a Deadbeat Solution

  • Qi, Chen;Tu, Pengfei;Wang, Peng;Zagrodnik, Michael
    • Journal of Power Electronics
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    • 제17권1호
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    • pp.76-87
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    • 2017
  • Finite-set predictive current control (FS-PCC) is advantageous for power converters due to its high dynamic performance and has received increasing interest in multilevel inverters. Among multilevel inverter topologies, the cascaded H-bridge (CHB) inverter is popular and mature in the industry. However, a main drawback of FS-PCC is its large computational burden, especially for the application of CHB inverters. In this paper, an FS-PCC method based on a deadbeat solution for three-phase zero-common-mode-voltage CHB inverters is proposed. In the proposed method, an inverse model of the load is utilized to calculate the reference voltage based on the reference current. In addition, a cost function is directly expressed in the terms of the voltage errors. An optimal control actuation is selected by minimizing the cost function. In the proposed method, only three instead of all of the control actuations are used for the calculations in one sampling period. This leads to a significant reduction in computations. The proposed method is tested on a three-phase 5-level CHB inverter. Simulation and experimental results show a very similar and comparable control performance from the proposed method compared with the traditional FS-PCC method which evaluates the cost function for all of the control actuations.

A Classification Algorithm Based on Data Clustering and Data Reduction for Intrusion Detection System over Big Data

  • Wang, Qiuhua;Ouyang, Xiaoqin;Zhan, Jiacheng
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제13권7호
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    • pp.3714-3732
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    • 2019
  • With the rapid development of network, Intrusion Detection System(IDS) plays a more and more important role in network applications. Many data mining algorithms are used to build IDS. However, due to the advent of big data era, massive data are generated. When dealing with large-scale data sets, most data mining algorithms suffer from a high computational burden which makes IDS much less efficient. To build an efficient IDS over big data, we propose a classification algorithm based on data clustering and data reduction. In the training stage, the training data are divided into clusters with similar size by Mini Batch K-Means algorithm, meanwhile, the center of each cluster is used as its index. Then, we select representative instances for each cluster to perform the task of data reduction and use the clusters that consist of representative instances to build a K-Nearest Neighbor(KNN) detection model. In the detection stage, we sort clusters according to the distances between the test sample and cluster indexes, and obtain k nearest clusters where we find k nearest neighbors. Experimental results show that searching neighbors by cluster indexes reduces the computational complexity significantly, and classification with reduced data of representative instances not only improves the efficiency, but also maintains high accuracy.

동적시스템의 차수 줄임을 위한 주상태의 최적선택 (Optimal Selection of Master States for Order Reduction)

  • 오동호;박영진
    • 소음진동
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    • 제4권1호
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    • pp.71-82
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    • 1994
  • We propose a systematic method to select the master states, which are retained in the reduced model after the order reduction process. The proposed method is based on the fact that the range space of right eigenvector matrix is spanned by orthogonal base vectors, and tries to keep the orthogonality of the submatrix of the base vector matrix as much as possible during the reduction process. To quentify the skewness of that submatrix, we define "Absolute Singularity Factor(ASF)" based on its singular values. While the degree of observability is concerned with estimation error of state vector and up to n'th order derivatives, ASF is related only to the minimum state estimation error. We can use ASF to evaluate the estimation performance of specific partial measurements compared with the best case in which all the state variables are identified based on the full measurements. A heuristic procedure to find suboptimal master states with reduced computational burden is also proposed. proposed.

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OFDM 통신방식에서 PAPR 감소를 위한 SDM 방식 (A SDM Method for the PAPR Reduction in the OFDM Communication System)

  • 유호진;유흥균
    • 한국전자파학회논문지
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    • 제14권3호
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    • pp.244-252
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    • 2003
  • 본 논문에서는 OFDM(Orthogonal Frequency Division Multiplexing)통신 시스템에서 발생하는 중요한 문제점인 PAPR(Peak to Average Power Ratio)을 저감하기 위하여 새로운 SDM(Subband Division Method) 방식을 제안한다. 제안 방식은 데이터 서브 블록을 몇 개의 서브블록으로 나누어 PAPR이 낮게 되는 서브블록까지 전송하고, 나머지 서브 블록은 다음번에 전송하는 방식이다. 적용 알고리즘에 따라 SDM 1과 SDM 2를 제안하였고 각각 성능을 분석 비교하였다. 제안 방식은 기존의 PAPR 저감 기법중 가장 좋은 PTS 방식과 비교하였을 경우, 비슷한 PAPR 저감성능을 보이면서도, 상당한 계산량 감소를 보인다.

Peak-to-Average Power Ratio Reduction of OFDM Signals Using Evolutionary Techniques

  • Pantos, George D.;Karamalis, Panagiotis D.;Constantinou, Philip
    • Journal of Communications and Networks
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    • 제10권3호
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    • pp.233-238
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    • 2008
  • In this paper, the application of genetic algorithms (GAs) for orthogonal frequency division multiplexing (OFDM) signal peak-to-average power ratio (PAPR) reduction is investigated. A GA is applied in order to enhance the performance of some known techniques for OFDM PAPR reduction and the potential benefits are analyzed. Using the proposed techniques, the system designer can take advantage of the GA versatility, robustness, and adaptability to specific system requirements, in order to achieve a convenient trade-off between effectiveness and computational burden.