• Title/Summary/Keyword: Weighting analysis

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Instance Based Learning Revisited: Feature Weighting and its Applications

  • Song Doo-Heon;Lee Chang-Hun
    • Journal of Korea Multimedia Society
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    • v.9 no.6
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    • pp.762-772
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    • 2006
  • Instance based learning algorithm is the best known lazy learner and has been successfully used in many areas such as pattern analysis, medical analysis, bioinformatics and internet applications. However, its feature weighting scheme is too naive that many other extensions are proposed. Our version of IB3 named as eXtended IBL (XIBL) improves feature weighting scheme by backward stepwise regression and its distance function by VDM family that avoids overestimating discrete valued attributes. Also, XIBL adopts leave-one-out as its noise filtering scheme. Experiments with common artificial domains show that XIBL is better than the original IBL in terms of accuracy and noise tolerance. XIBL is applied to two important applications - intrusion detection and spam mail filtering and the results are promising.

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Generalized optimal active control algorithm with weighting matrix configuration, stability and time-delay

  • Cheng, Franklin Y.;Tian, Peter
    • Structural Engineering and Mechanics
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    • v.1 no.1
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    • pp.119-135
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    • 1993
  • The paper presents a generalized optimal active control algorithm for earthquake-resistant structures. The study included the weighting matrix configuration, stability, and time-delays for achieving control effectiveness and optimum solution. The sensitivity of various time-delays in the optimal solution is investigated for which the stability regions are determined. A simplified method for reducing the influence of time-delay on dynamic response is proposed. Numerical examples illustrate that the proposed optimal control algorithm is advantageous over others currently in vogue. Its feedback control law is independent of the time increment, and its weighting matrix can be flexibly selected and adjusted at any time during the operation of the control system. The examples also show that the weighting matrix based on pole placement approach is superior to other weighting matrix configurations for its self-adjustable control effectiveness. Using the time-delay correction method can significantly reduce the influence of time-delays on both structural response and required control force.

Analysis of the Typical Meteorological Data and the Weighting Factor of TRY (표준기상데이터 형식 분석 및 TRY 가중치 적용)

  • Yoo, Ho-Chun;Lee, Gwan-ho;Park, So-Hee;Kim, Kyoung-Ryul
    • Journal of the Korean Solar Energy Society
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    • v.27 no.4
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    • pp.157-165
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    • 2007
  • Typical meteorological data is fundamental to computer simulation introduced for environment-friendly architecture designs. Therefore, in order to improve accuracy of computer simulation, typical meteorological data should be established. By examining how to choose typical meteorological data, this study selected the optimized weight factor for TRY where weighting factor was not clearly set. As a result, the same weighting factor was applied to each climatic element and TRY data where the weight factor was applied could have the distribution very similar to measurement data. The weighting factor is considered to reflect geographical characteristics of Seoul and applied climatic elements.

An Application of Case-Based Reasoning in Forecasting a Successful Implementation of Enterprise Resource Planning Systems : Focus on Small and Medium sized Enterprises Implementing ERP (성공적인 ERP 시스템 구축 예측을 위한 사례기반추론 응용 : ERP 시스템을 구현한 중소기업을 중심으로)

  • Lim Se-Hun
    • Journal of Information Technology Applications and Management
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    • v.13 no.1
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    • pp.77-94
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    • 2006
  • Case-based Reasoning (CBR) is widely used in business and industry prediction. It is suitable to solve complex and unstructured business problems. Recently, the prediction accuracy of CBR has been enhanced by not only various machine learning algorithms such as genetic algorithms, relative weighting of Artificial Neural Network (ANN) input variable but also data mining technique such as feature selection, feature weighting, feature transformation, and instance selection As a result, CBR is even more widely used today in business area. In this study, we investigated the usefulness of the CBR method in forecasting success in implementing ERP systems. We used a CBR method based on the feature weighting technique to compare the performance of three different models : MDA (Multiple Discriminant Analysis), GECBR (GEneral CBR), FWCBR (CBR with Feature Weighting supported by Analytic Hierarchy Process). The study suggests that the FWCBR approach is a promising method for forecasting of successful ERP implementation in Small and Medium sized Enterprises.

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AN ALGORITHM FOR DETERMINING THE WEIGHTING MATRICES OF THE QUADRATIC PERFORMANCE INDEX IN OPTIMAL CONTROL (최적제어 설계에 있어서의 2차형 하중행렬의 한 결정법)

  • Hwa, Chang-Sun;Kim, Chung-Tek
    • Proceedings of the KIEE Conference
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    • 1989.11a
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    • pp.407-410
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    • 1989
  • Optimizing transient response for both tracking reference signals and disturbance rejection is determined by the poles and zeros of the transfer function. Thus, optimal pole assignment and how should weighting matrix for the performance index be chosen is very important to achieve optimum transient response. This paper focus its attention on the choosing and analysis of weighting matrix for optimum pole assignment. Optimum pole assignment is defined for linear time-invariant continuous systems.

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A Proposal of the Evaluation Method for Rock Slope Stability Using Logistic Regression Analysis (로지스틱 회귀분석을 통한 암반사면의 안정성 평가법 제안)

  • 이용희;김종열
    • Tunnel and Underground Space
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    • v.14 no.2
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    • pp.133-141
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    • 2004
  • Through the many site investigations, different methods for evaluating stability of rock slopes have been proposed. Those methods, however, may lead to different results depending on the subjective judgments associated with the selection of the evaluation items and the application of weighting factor. Accordingly, binary logistic regression analysis was carried out to ensure fair appliction of the weighting factor, leading to an equation for evaluating the stability of rock slopes.

Design and Performance Analysis of the SPW Method for PAPR Reduction in OFDM System (OFDM 시스템에서 PAPR 처감을 위한 SPW 방식의 설계와 성능 분석)

  • 이재은;유흥균;정영호;함영권
    • The Journal of Korean Institute of Electromagnetic Engineering and Science
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    • v.14 no.7
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    • pp.677-684
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    • 2003
  • This paper addresses the subblock phase weighting(SPW) method to reduce the PAPR in OFDM system. This method divides the input block of OFDM signal into many subblocks and lower the peak power by weighting the phase of each subblocks properly. SPW method can be realized by only one IFFT. PAPR reduction performance is novelly examined when the adjacent, interleaved and random subblock partitioning schemes are used in the SPW system. The random subblock partition scheme has the most effective. More subblocks can effectively reduce the PAPR, but there is a problem that the processing time of iteration is increased. We propose a new weighting factor combination of the complementary sequence characteristic with threshold technique. OFDM data can be recovered by the inserted side information of weighting factor in the feed forward type. Also, BER performance of this SPW system is analyzed when error happens in the side information.

Partly Random Multiple Weighting Matrices Selection for Orthogonal Random Beamforming

  • Tan, Li;Li, Zhongcai;Xu, Chao;Wang, Desheng
    • Journal of Communications and Networks
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    • v.18 no.6
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    • pp.892-901
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    • 2016
  • In the multi-user multiple-input multiple-output (MIMO) system, orthogonal random beamforming (ORBF) scheme is proposed to serve multiple users simultaneously in order to achieve the multi-user diversity gain. The opportunistic space-division multiple access system (OSDMA-S) scheme performs multiple weighting matrices during the training phase and chooses the best weighting matrix to be used to broadcast data during the transmitting phase. The OSDMA-S scheme works better than the original ORBF by decreasing the inter-user interference during the transmitting phase. To save more time in the training phase, a partly random multiple weighting matrices selection scheme is proposed in this paper. In our proposed scheme, the Base Station does not need to use several unitary matrices to broadcast pilot symbol. Actually, only one broadcasting operation is needed. Each subscriber generates several virtual equivalent channels with a set of pre-saved unitary matrices and the channel status information gained from the broadcasting operation. The signal-to-interference and noise ratio (SINR) of each beam in each virtual equivalent channel is calculated and fed back to the base station for the weighting matrix selection and multi-user scheduling. According to the theoretical analysis, the proposed scheme relatively expands the transmitting phase and reduces the interactive complexity between the Base Station and subscribers. The asymptotic analysis and the simulation results show that the proposed scheme improves the throughput performance of the multi-user MIMO system.

A SEXTIC-ORDER SIMPLE-ROOT FINDER WITH RATIONAL WEIGHTING FUNCTIONS OF DERIVATIVE-TO-DERIVATIVE RATIOS

  • Kim, Young Ik
    • Journal of the Chungcheong Mathematical Society
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    • v.27 no.4
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    • pp.753-762
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    • 2014
  • A three-step sextic simple-root finder is constructed with the use of weighting functions of derivative-to-derivative ratios. Their convergence and computational properties are investigated along with concrete numerical examples to verify the theoretical analysis.

Practical Validity of Weighting Methods : A Comparative Analysis Using Bootstrapping (부트스트랩핑을 이용한 가중치 결정방법의 실질적 타당성 비교)

  • Jeong, Ji-Ahn;Cho, Sung-Ku
    • Journal of Korean Institute of Industrial Engineers
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    • v.26 no.1
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    • pp.27-35
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    • 2000
  • For a weighting method to be practically valid, it should produce weights which coincide with the relative importance of attributes perceived by the decision maker. In this paper, 'bootstrapping' is used to compare the practical validities of five weighting methods frequently used; the rank order centroid method, the rank reciprocal method, the rank sum method, the entropic method, and the geometric mean method. Bootstrapping refers to the procedure where the analysts allow the decision maker to make careful judgements on a series of similar cases, then infer statistically what weights he was implicitly using to arrive at the particular ranking. The weights produced by bootstrapping can therefore be regarded as well reflecting the decision maker's perceived relative importances. Bootstrapping and the five weighting methods were applied to a job selection problem. The results showed that both the rank order centroid method and the rank reciprocal method had higher level of practical validity than the other three methods, though a large difference could not be found either in the resulting weights or in the corresponding solutions.

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