• Title/Summary/Keyword: Error patterns

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Comparison of time series clustering methods and application to power consumption pattern clustering

  • Kim, Jaehwi;Kim, Jaehee
    • Communications for Statistical Applications and Methods
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    • v.27 no.6
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    • pp.589-602
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    • 2020
  • The development of smart grids has enabled the easy collection of a large amount of power data. There are some common patterns that make it useful to cluster power consumption patterns when analyzing s power big data. In this paper, clustering analysis is based on distance functions for time series and clustering algorithms to discover patterns for power consumption data. In clustering, we use 10 distance measures to find the clusters that consider the characteristics of time series data. A simulation study is done to compare the distance measures for clustering. Cluster validity measures are also calculated and compared such as error rate, similarity index, Dunn index and silhouette values. Real power consumption data are used for clustering, with five distance measures whose performances are better than others in the simulation.

Adaptive mesh refinement/recovery strategy for FEA

  • Choi, Chang-Koon;Lee, Eun-Jin;Yu, Won-Jin
    • Structural Engineering and Mechanics
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    • v.17 no.3_4
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    • pp.379-391
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    • 2004
  • This paper deals with the development of h-version adaptive mesh refinement and recovery strategy using variable-node elements and its application to various engineering field problems with 2D quadrilateral and 3D hexahedral models. The variable-node elements which have variable mid-side nodes on edges or faces are effectively used in overcoming some problems in connecting the different layer patterns of the transition zone between the refined and coarse mesh. A modified recovery technique of gradients adequate for variable-node elements and proper selection of error norms for each engineering field problems are proposed. In the region in which the error is greater than the permissible refinement error, the mesh is locally refined by subdivision. Reversely, in some parts of the domain having the error smaller than the permissible recovery error, the mesh is locally recovered (coarsened) by combination. Hierarchical structures (e.g. quadtrees and octrees) and element-based storage structures are composed to perform this adaptive process of refinement and recovery. Some numerical examples of a 3D heat conduction analysis of the concrete with hydration heat and a 2D flow analysis of vortex shedding show effectiveness and validity of the proposed scheme.

Optimum Design of the Microphone Sensor Array for 3D TDOA Positioning System (3차원 TDOA 위치인식 시스템의 마이크 센서 배열 최적 설계)

  • Oh, Jongtaek
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.14 no.1
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    • pp.31-36
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    • 2014
  • A study on the indoor positioning system has been active recently for the location based service indoors. In the 3 dimensional positioning system based on the acoustic signal and TDOA technology, the error characteristics of the estimated source position would be changed depending on the number of microphones and the pattern of the microphone array. In this paper, the estimated position error according to the measured distance error between the microphones and the signal source is analyzed, and the optimum microphone array is decided considering the estimated position error patterns and the total amount of the estimated position error.

Effects of Viewing Angle on the Estimation of Joint Angles in the 2-dimensional Plane (2차원 면에서의 자세 관측시 시야각이 관절각 추정에 미치는 영향)

  • Lee, In-Seok
    • Journal of the Ergonomics Society of Korea
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    • v.25 no.2
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    • pp.51-62
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    • 2006
  • In assessing risks related to working posture, pictures of postures are taken from various directions, which can be a source of observation error. Joint postures of the neck, lower back, knee, shoulder, and elbow were taken from 7 different viewing angles and 19 observers estimated joint angles by observing the pictures in 2-dimensional display. The joint angles were also measured using an optoelectronic motion measurement system. The estimation error increased as the viewing angle varies from the right side of the human body, but the patterns differ according to which joint angles were being observed. Guidelines to increase the validity of observation of joint angles were presented based on the results. In general, it is recommended to maintain the viewing angle within 20 degrees from the right side of the human body, while different ranges of viewing angle are recommended for each joint angle.

Data Randomization Scheme for Endurance Enhancement and Interference Mitigation of Multilevel Flash Memory Devices

  • Cha, Jaewon;Kang, Sungho
    • ETRI Journal
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    • v.35 no.1
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    • pp.166-169
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    • 2013
  • In this letter, we propose a data randomization scheme for endurance and interference mitigation of deeply-scaled multilevel flash memory. We address the relationships between data patterns and the raw bit error rate. An on-chip pseudorandom generator composed of an address-based seed location decoder is developed and evaluated with respect to uniformity. Experiments performed with 2x-nm and 4x-nm NAND flash memory devices illustrate the effectiveness of our scheme. The results show that the error rate is reduced up to 86% compared to that of a conventional cycling scheme. Accordingly, the endurance phenomenon can be mitigated through analysis of interference that causes tech shrinkage.

HAI Control for Speed Control of SPMSM Drive (SPMSM 드라이브의 속도제어를 위한 HAI 제어)

  • Lee, Hong-Gyun;Lee, Jung-Chul;Chung, Dong-Hwa
    • The Transactions of the Korean Institute of Electrical Engineers P
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    • v.54 no.1
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    • pp.8-14
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    • 2005
  • This paper is proposed hybrid artificial intelligent(HAI) controller for speed control of surface permanent magnet synchronous motor(SPMSM) drive. The design of this algorithm based on HAI controller that is implemented using fuzzy control and neural network. This controller uses fuzzy rule as training patterns of a neural network. Also, this controller uses the back-propagation method to adjust the weights between the neurons of neural network in order to minimize the error between the command output and actual output. A model reference adaptive scheme is proposed in which the adaptation mechanism is executed by fuzzy logic based on the error and change of error measured between the motor speed and output of a reference model. The control performance of the HAI controller is evaluated by analysis for various operating conditions. The results of analysis prove that the proposed control system has strong high performance and robustness to parameter variation, and steady-state accuracy and transient response.

Adaptive FNN Controller for High Performance Control of Induction Motor Drive (유도전동기 드라이브의 고성능 제어를 위한 적응 FNN 제어기)

  • 이정철;이홍균;정동화
    • The Transactions of the Korean Institute of Electrical Engineers B
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    • v.53 no.9
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    • pp.569-575
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    • 2004
  • This paper is proposed adaptive fuzzy-neural network(FNN) controller for high performance of induction motor drive. The design of this algorithm based on FNN controller that is implemented using fuzzy control and neural network. This controller uses fuzzy rule as training patterns of a neural network. Also, this controller uses the back-propagation method to adjust the weights between the neurons of neural network in order to minimize the error between the command output and actual output. A model reference adaptive scheme is proposed in which the adaptation mechanism is executed by fuzzy logic based on the error and change of error measured between the motor speed and output of a reference model. The control Performance of the adaptive FNN controller is evaluated by analysis for various operating conditions. The results of analysis prove that the proposed control system has strong high performance and robustness to parameter variation. and steady- state accuracy and transient response.

High Performance of Induction Motor Drive with HAl Controller (HAI 제어기에 의한 유도전동기 드라이브의 고성능 제어)

  • Nam, Su-Myeong;Choi, Jung-Sik;Ko, Jae-Sub;Chung, Dong-Hwa
    • Proceedings of the KIEE Conference
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    • 2005.10b
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    • pp.570-572
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    • 2005
  • This paper is proposed adaptive hybrid artificial intelligent(HAI) controller for high performance of induction motor drive. The design of this algorithm based on fuzzy-neural network(FNN) controller that is implemented using fuzzy control and neural network. This controller uses fuzzy rule as training patterns of a neural network. Also, this controller uses the back-propagation method to adjust the weights between the neurons of neural network in order to minimize the error between the command output and actual output. A model reference adaptive scheme is proposed in which the adaptation mechanism is executed by fuzzy logic based on the error and change of error measured between the motor speed and output of a reference model. The control performance of the adaptive FNN controller is evaluated by analysis for various operating conditions. The results of experiment prove that the proposed control system has strong high performance and robustness to parameter variation, and steady-state accuracy and transient response.

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Environment-Based Ranging Error Correction Technique Using IEEE 802.15.4a CSS PHY (IEEE 802.15.4a CSS PHY를 이용한 환경기반 거리측정오차 보정 기법)

  • Nam, Min-Seok;Park, Young-Kyun;Nam, Young Jin;Lee, Dong-Ha;Kang, Jin-Kyu;Lee, Sang-Cheol
    • IEMEK Journal of Embedded Systems and Applications
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    • v.4 no.4
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    • pp.148-155
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    • 2009
  • Precise localization heavily relies on the accuracy of its underlying ranging technique. It has been known that the Chirp Spread Spectrum (CSS) defined in the IEEE 802.15.4a provides more dependable ranging accuracy than the Received Signal Strength Indicator (RSSI) in the IEEE 802.15.4. This paper examines the accuracy of the CSS-based ranging technique in the indoor/outdoor environments and discovers its consistent inaccuracy in different environments. Next, it proposes an error-correction architecture for the CSS-based ranging technique that exploits the per-environment consistent inaccuracy information and user visiting patterns (represented by weights for each environment).

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