• Title/Summary/Keyword: Hybrid index

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Choice of weights in a hybrid volatility based on high-frequency realized volatility (고빈도 금융 시계열 실현 변동성을 이용한 가중 융합 변동성의 가중치 선택)

  • Yoon, J.E.;Hwang, S.Y.
    • The Korean Journal of Applied Statistics
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    • v.29 no.3
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    • pp.505-512
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    • 2016
  • The paper is concerned with high frequency financial time series. A weighted hybrid volatility is suggested to compute daily volatilities based on high frequency data. Various realized volatility (RV) computations are reviewed and the weights are chosen by minimizing the differences between the hybrid volatility and the realized volatility. A high frequency time series of KOSPI200 index is illustrated via QLIKE and Theil-U statistics.

The hybrid uncertain neural network method for mechanical reliability analysis

  • Peng, Wensheng;Zhang, Jianguo;You, Lingfei
    • International Journal of Aeronautical and Space Sciences
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    • v.16 no.4
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    • pp.510-519
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    • 2015
  • Concerning the issue of high-dimensions, hybrid uncertainties of randomness and intervals including implicit and highly nonlinear limit state function, reliability analysis based on the hybrid uncertainty reliability mode combining with back propagation neural network (HU-BP neural network) is proposed in this paper. Random variables and interval variables are as input layer of the neural network, after the training and approximation of the neural network, the response variables are obtained through the output layer. Reliability index is calculated by solving the optimization model of the most probable point (MPP) searching in the limit state band. Two numerical cases are used to demonstrate the method proposed in this paper, and finally the method is employed to solving an engineering problem of the aerospace friction plate. For this high nonlinear, small failure probability problem with interval variables, this method could achieve a good analysis result.

Hybrid Fuzzy Controller Based on Control Parameter Estimation Mode Using Genetic Algorithms (유전자 알고리즘을 이용한 제어파라미터 추정모드기반 HFC)

  • Lee, Dae-Keun;Oh, Sung-Kwun;Jang, Sung-Whan
    • Proceedings of the KIEE Conference
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    • 2000.07d
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    • pp.2545-2547
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    • 2000
  • In this paper, a hybrid fuzzy controller using genetic algorithm based on parameter estimation mode to obtain optimal control parameter is presented. First, The control input for the system in the HFC is a convex combination of the FLC's output in transient state and PID's output in steady state by a fuzzy variable, namely, membership function of weighting coefficient. Second, genetic algorithms is presented to automatically improve the performance of hybrid fuzzy controller utilizing the conventional methods for finding PID parameters and estimation mode of scaling factor. The algorithms estimates automatically the optimal values of scaling factors, PID parameters and membership function parameters of fuzzy control rules according to the rate of change and limitation condition of control input. Computer simulations are conducted to evaluate the performance of proposed hybrid fuzzy controller. ITAE, overshoot and rising time are used as a performance index of controller.

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Multi-level Scheduling Algorithm Based on Storm

  • Wang, Jie;Hang, Siguang;Liu, Jiwei;Chen, Weihao;Hou, Gang
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.10 no.3
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    • pp.1091-1110
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    • 2016
  • Hybrid deployment under current cloud data centers is a combination of online and offline services, which improves the utilization of the cluster resources. However, the performance of the cluster is often affected by the online services in the hybrid deployment environment. To improve the response time of online service (e.g. search engine), an effective scheduling algorithm based on Storm is proposed. At the component level, the algorithm dispatches the component with more influence to the optimal performance node. Inside the component, a reasonable resource allocation strategy is used. By searching the compressed index first and then filtering the complete index, the execution speed of the component is improved with similar accuracy. Experiments show that our algorithm can guarantee search accuracy of 95.94%, while increasing the response speed by 68.03%.

A hybrid evaluation of information entropy meta-heuristic model and unascertained measurement theory for tennis motion tracking

  • Zhong, Yongfeng;Liang, Xiaojun
    • Advances in nano research
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    • v.12 no.3
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    • pp.263-279
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    • 2022
  • In this research, the physical education training quality was investigated using the entropy model to compute variance associated with a random value (a strong tool). The entropy and undefined estimation principles are used to extract the greatest entropy of information dependent on the index system. In the study of tennis motion tracking from a dynamic viewpoint, such stages are utilized to improve the perception of the players' achievement (Lv et al. 2020). Six female tennis players served on the right side (50 cm from the T point). The initial flat serve from T point was the movement under consideration, and the entropy was utilized to weigh all indications. As a result, a multi-index measurement vector is stabilized, followed by the confidence level to determine the structural plane establishment range. As a result, the use of the unascertained measuring technique of information entropy showed an excellent approach to assessing athlete performance more accurately than traditional ways, enabling coaches and athletes to enhance their movements successfully.

Intelligent hybrid controlled structures with soil-structure interaction

  • Zhang, X.Z.;Cheng, F.Y.;Lou, M.L.
    • Structural Engineering and Mechanics
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    • v.17 no.3_4
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    • pp.573-591
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    • 2004
  • A hybrid control system is presented for seismic-resistant building structures with and without soil-structure interaction (SSI). The hybrid control is a damper-actuator-bracing control system composed of passive and active controllers. An intelligent algorithm is developed for the hybrid system, in which the passive damper is designed for minor and moderate earthquakes and the active control is designed to activate when the structural response is greater than a given threshold quantity. Thus, the external energy for active controller can be optimally utilized. In the control of a multistory building, the controller placement is determined by evaluating the optimal location index (OLI) calculated from six earthquake sources. In the study, the soil-structure interaction is considered both in frequency domain and time domain analyses. It is found that the interaction can significantly affect the control effectiveness. In the hybrid control algorithm with intelligent strategy, the working stages of passive and active controllers can be different for a building with and without considering SSI. Thus SSI is essential to be included in predicting the response history of a controlled structure.

Low Complexity Hybrid Interpolation Algorithm using Weighted Edge Detector (가중치 윤곽선 검출기를 이용한 저 복잡도 하이브리드 보간 알고리듬)

  • Kwon, Hyeok-Jin;Jeon, Gwang-Gil;Jeong, Je-Chang
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.32 no.3C
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    • pp.241-248
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    • 2007
  • In predictive image coding, a LS (Least Squares)-based adaptive predictor is an efficient method to improve image edge predictions. This paper proposes a hybrid interpolation with weighted edge detector. A hybrid approach of switching between bilinear interpolation and EDI (Edge-Directed Interpolation) is proposed in order to reduce the overall computational complexity The objective and subjective quality is also similar to the bilinear interpolation and EDI. Experimental results demonstrate that this hybrid interpolation method that utilizes a weighted edge detector can achieve reduction in complexity with minimal degradation in the interpolation results.

An Efficient Multidimensional Index Structure for Parallel Environments

  • Bok Koung-Soo;Song Seok-Il;Yoo Jae-Soo
    • International Journal of Contents
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    • v.1 no.1
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    • pp.50-58
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    • 2005
  • Generally, multidimensional data such as image and spatial data require large amount of storage space. There is a limit to store and manage those large amounts of data in single workstation. If we manage the data on parallel computing environment which is being actively researched these days, we can get highly improved performance. In this paper, we propose a parallel multidimensional index structure that exploits the parallelism of the parallel computing environment. The proposed index structure is nP(processor)-nxmD(disk) architecture which is the hybrid type of nP-nD and 1P-nD. Its node structure in-creases fan-out and reduces the height of an index. Also, a range search algorithm that maximizes I/O parallelism is devised, and it is applied to k-nearest neighbor queries. Through various experiments, it is shown that the proposed method outperforms other parallel index structures.

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A New Topology of Four-Level Hybrid Half-Bridge Flying-Capacitor Inverter (4-레벨 하이브리드 하프 브리지 플라잉 캐패시터 인버터의 새로운 토폴로지)

  • Pribadi, Jonathan;Lee, Dong-Choon
    • Proceedings of the KIPE Conference
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    • 2019.07a
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    • pp.315-316
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    • 2019
  • This paper proposes the operation scheme and control method for a four-level hybrid half-bridge flying-capacitor inverter (4L-HHBFCI). With in-phase disposition level-shifted modulation (IPD), the flying capacitor voltage ripple is less than 1% of the reference value, while the line-to-line voltage total harmonic distortion is 23.27% at unity modulation index. The performance and effectiveness of the proposed inverter operation have been verified by simulation results.

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