• 제목/요약/키워드: Data Weighting Scheme

검색결과 47건 처리시간 0.028초

RC structural system control subjected to earthquakes and TMD

  • Jenchung Shao;M. Nasir Noor;P. Ken;Chuho Chang;R. Wang
    • Structural Engineering and Mechanics
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    • 제89권2호
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    • pp.213-223
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    • 2024
  • This paper proposes a composite design of fuzzy adaptive control scheme based on TMD RC structural system and the gain of two-dimensional fuzzy control is controlled by parameters. Monitoring and learning in LMI then produces performance indicators with a weighting matrix as a function of cost. It allows to control the trade-off between the two efficiencies by adjusting the appropriate weighting matrix. The two-dimensional Boost control model is equivalent to the LMI-constrained multi-objective optimization problem under dual performance criteria. By using the proposed intelligent control model, the fuzzy nonlinear criterion is satisfied. Therefore, the data connection can be further extended. Evaluation of controller performance the proposed controller is compared with other control techniques. This ensures good performance of the control routines used for position and trajectory control in the presence of model uncertainties and external influences. Quantitative verification of the effectiveness of monitoring and control. The purpose of this article is to ensure access to adequate, safe and affordable housing and basic services. Therefore, it is assumed that this goal will be achieved in the near future through the continuous development of artificial intelligence and control theory.

Minimizing Sensing Decision Error in Cognitive Radio Networks using Evolutionary Algorithms

  • Akbari, Mohsen;Hossain, Md. Kamal;Manesh, Mohsen Riahi;El-Saleh, Ayman A.;Kareem, Aymen M.
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제6권9호
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    • pp.2037-2051
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    • 2012
  • Cognitive radio (CR) is envisioned as a promising paradigm of exploiting intelligence for enhancing efficiency of underutilized spectrum bands. In CR, the main concern is to reliably sense the presence of primary users (PUs) to attain protection against harmful interference caused by potential spectrum access of secondary users (SUs). In this paper, evolutionary algorithms, namely, particle swarm optimization (PSO) and genetic algorithm (GA) are proposed to minimize the total sensing decision error at the common soft data fusion (SDF) centre of a structurally-centralized cognitive radio network (CRN). Using these techniques, evolutionary operations are invoked to optimize the weighting coefficients applied on the sensing measurement components received from multiple cooperative SUs. The proposed methods are compared with each other as well as with other conventional deterministic algorithms such as maximal ratio combining (MRC) and equal gain combining (EGC). Computer simulations confirm the superiority of the PSO-based scheme over the GA-based and other conventional MRC and EGC schemes in terms of detection performance. In addition, the PSO-based scheme also shows promising convergence performance as compared to the GA-based scheme. This makes PSO an adequate solution to meet real-time requirements.

SMAP 토양수분을 위한 Landsat 기반 상세화 기법 개발 (Development of Landsat-based Downscaling Algorithm for SMAP Soil Moisture Footprints)

  • 이태화;김상우;신용철
    • 한국농공학회논문집
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    • 제60권4호
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    • pp.49-54
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    • 2018
  • With increasing satellite-based RS(Remotely Sensed) techniques, RS soil moisture footprints have been providing for various purposes at the spatio-temporal scales in hydrology, agriculture, etc. However, their coarse resolutions still limit the applicability of RS soil moisture to field regions. To overcome these drawbacks, the LDA(Landsat-based Downscaling Algorithm) was developed to downscale RS soil moisture footprints from the coarse- to finer-scales. LDA estimates Landsat-based soil moisture($30m{\times}30m$) values in a spatial domain, and then the weighting values based on the Landsat-based soil moisture estimates were derived at the finer-scale. Then, the coarse-scale RS soil moisture footprints can be downscaled based on the derived weighting values. The LW21(Little Washita) site in Oklahoma(USA) was selected to validate the LDA scheme. In-situ soil moisture data measured at the multiple sampling locations that can reprent the airborne sensing ESTAR(Electronically Scanned Thinned Array Radiometer, $800m{\times}800m$) scale were available at the LW21 site. LDA downscaled the ESTAR soil moisture products, and the downscaled values were validated with the in-situ measurements. The soil moisture values downscaled from ESTAR were identified well with the in-situ measurements, although uncertainties exist. Furthermore, the SMAP(Soil Moisture Active & Passive, $9km{\times}9km$) soil moisture products were downscaled by the LDA. Although the validation works have limitations at the SMAP scale, the downscaled soil moisture values can represent the land surface condition. Thus, the LDA scheme can downscale RS soil moisture products with easy application and be helpful for efficient water management plans in hydrology, agriculture, environment, etc. at field regions.

A novel classification approach based on Naïve Bayes for Twitter sentiment analysis

  • Song, Junseok;Kim, Kyung Tae;Lee, Byungjun;Kim, Sangyoung;Youn, Hee Yong
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제11권6호
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    • pp.2996-3011
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    • 2017
  • With rapid growth of web technology and dissemination of smart devices, social networking service(SNS) is widely used. As a result, huge amount of data are generated from SNS such as Twitter, and sentiment analysis of SNS data is very important for various applications and services. In the existing sentiment analysis based on the $Na{\ddot{i}}ve$ Bayes algorithm, a same number of attributes is usually employed to estimate the weight of each class. Moreover, uncountable and meaningless attributes are included. This results in decreased accuracy of sentiment analysis. In this paper two methods are proposed to resolve these issues, which reflect the difference of the number of positive words and negative words in calculating the weights, and eliminate insignificant words in the feature selection step using Multinomial $Na{\ddot{i}}ve$ Bayes(MNB) algorithm. Performance comparison demonstrates that the proposed scheme significantly increases the accuracy compared to the existing Multivariate Bernoulli $Na{\ddot{i}}ve$ Bayes(BNB) algorithm and MNB scheme.

전기 임피던스 단층촬영을 위한 지수적으로 가중된 최소자승법을 이용한 수정된 조정 Newton-Raphson 알고리즘 (Regularized Modified Newton-Raphson Algorithm for Electrical Impedance Tomography Based on the Exponentially Weighted Least Square Criterion)

  • 김경연;김봉석
    • 전기전자학회논문지
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    • 제4권2호
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    • pp.249-256
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    • 2000
  • 전기 임피던스 단층촬영에서는, 각기 다른 주입 전류패턴에 의해 유기된 경계면의 전압 값을 이용하여 다양한 복원 알고리즘에 의해 물체의 내부 저항률(전도율) 분포를 추정한다. 본 논문에서는, 부가적인 사전 정보를 soft 제약조건으로 비용함수에 추가하고, 비용함수의 가중행렬을 지수적으로 가중된 최소자승법에 근거하여 선택하는 수정된 조정 Newton-Raphson(mNR) 법을 제안한다. 32채널에 대한 컴퓨터 시뮬레이션 결과, 제안된 방법은 기존의 조정 mNR 법에 비해 계산부담은 약간 증가하지만 복원성능이 개선됨을 보인다.

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중도절단 회귀모형에서 역절단확률가중 방법 간의 비교연구 (A comparison study of inverse censoring probability weighting in censored regression)

  • 신정민;김형우;신승준
    • 응용통계연구
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    • 제34권6호
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    • pp.957-968
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    • 2021
  • 역중도절단확률가중(inverse censoring probability weighting, ICPW)은 생존분석에서 흔히 사용되는 방법이다. 중도절단 회귀모형과 같은 ICPW 방법의 응용에 있어서 중도절단 확률의 정확한 추정은 핵심적인 요소라고 할 수 있다. 본 논문에서는 중도절단 확률의 추정이 ICPW 기반 중도절단 회귀모형의 성능에 어떠한 영향을 주는지 모의실험을 통하여 알아보았다. 모의실험에서는 Kaplan-Meier 추정량, Cox 비례위험(proportional hazard) 모형 추정량, 그리고 국소 Kaplan-Meier 추정량 세 가지를 비교하였다. 국소 KM 추정량에 대해서는 차원의 저주를 피하기 위해 공변량의 차원축소 방법을 추가적으로 적용하였다. 차원축소 방법으로는 흔히 사용되는 주성분분석(principal component analysis, PCA)과 절단역회귀(sliced inverse regression)방법을 고려하였다. 그 결과 Cox 비례위험 추정량이 평균 및 중위수 중도절단 회귀모형 모두에서 중도절단 확률을 추정하는 데 가장 좋은 성능을 보여주었다.

DEA에 의한 다속성 품질의 평가방법에 관한 연구 -전기보온솥의 사례를 중심으로- (Evaluation method of multi-attribute quality using data envelopment analysis)

  • 이진춘
    • 품질경영학회지
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    • 제25권2호
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    • pp.169-188
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    • 1997
  • The purpose of this study is concerned with suggesting a new a, pp.oach to evaluating the overall product quality in the sense of the relative efficiency of products, whose quality is measured with 8-dimensional attributes, suggested by Garvin. The attributes included 8 quality measures, that is, performance, features, reliability, conformance, durability, serviceabilit, aesthetics, and perceived quality. This study, also, introduced DEA(Data Envelopment Analysis) as an evaluation tool to tackle the problem of how to measure one product against another when each product can be measured along a number of dimensions, and given that there exists no a priori satisfactory weighting scheme to combine these dimensions into an overall rating for each products. In order to a, pp.y the DEA to evaluating the products, we must define two concepts, such as DMU(Decision Making Units) and input-output relationship. Finally, the suggested method in this study was validated through a case study of the electric jar, and this DEA a, pp.oach can be used in evaluating the other products with multi-attrribute quality.

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MODIS 해빙피복 기반의 가중치체계를 이용한 AMSR2 해빙면적비의 다운스케일링 (Downscaling of AMSR2 Sea Ice Concentration Using a Weighting Scheme Derived from MODIS Sea Ice Cover Product)

  • 안지혜;홍성욱;조재일;이양원
    • 대한원격탐사학회지
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    • 제30권5호
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    • pp.687-701
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    • 2014
  • 해빙은 일반적으로 지구기후 변화 과정을 이해할 수 있는 중요한 요인으로 인식되고 있으며, 기후변화 분석 및 예측을 위한 지구시스템 모델의 기반이 되는 중요한 인자로 대표되고 있다. 수 km 급의 작은 규모로 발생하는 해빙의 변화를 지속적으로 파악하기 위해서는 현재의 제한된 해빙자료로부터 보다 정확한 격자자료를 생산할 것이 요구된다. 본 연구에서는 Advanced Microwave Scanning Radiometer 2(AMSR2)의 월간 해빙면적비(Sea Ice Concentration: SIC) 자료와 상관성이 높은 Moderate Resolution Imaging Spectroradiometer(MODIS) 기반의 월간 해빙일수비율(sea ice days ratio)를 지점별 가중치로 이용하는 상세화 기법을 고안하여 10 km 공간해상도의 SIC 자료를 1 km 공간해상도로 상세화하였다. 오호츠크 해역의 분석 결과, 기존의 공간해상도 10 km 자료와 상세화한 1 km 자료에서 해빙면적은 동일하였으며, 월별 SIC 평균과 표준편차 역시 거의 동일한 값의 분포를 나타냈다. 또한 EOF 분석을 통해 기후모델의 SIC 재분석자료 및 AMSR2 상세화 전후 자료에서 공간적, 시간적 변동성의 주성분이 매우 유사한 경향을 가지는 것으로 나타났다. 본 연구에서 제시한 상세화 기법은 다른 백분율 등으로 표현되는 연속형 비율자료의 상세화에 적용 가능할 것으로 사료되며, 보다 세밀한 해상도의 SIC 자료를 제공함으로써 작은 규모로 발생하는 해빙변화 감시에 기여할 가능성을 보여준다.

단순한 시각적 하중에 의한 아다마르 영상부호화 (A Simple Human Visual Weighted Hadamard Transform Image Coding)

  • 황재정;이문호
    • 대한전자공학회논문지
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    • 제26권4호
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    • pp.98-105
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    • 1989
  • 선택적인 주파수 특성을 가지고 있는 인간의 시각 시스템(HVS)을 왈쉬함수로 표현되는 아다마르변환 영역에서 적용하였다. 아다마르 기본함수의 주파수 성분을 구하여 시각 시스템을 모델링하였으며 이때 오차측정의 기준으로서 저 전송율 변환 부호화기에서 중요한 요소인 블록 경계상의 오차와 평균자승 오차를 사용한 결과 인간이 가장 높은 감도를 갖는 공간 주파수는 이산 여현 변환의 경우보다 높게 나타났다. 부호화기에서 HVS 모델을 적용하여 시각적 감도가 높거나 중요한 정보만을 전송하고 북호화기에서는 역하중이 없는 방법을 제시하였다. 블록과 블록이 교차하는 영역에서 특히 크게 나타나는 오차를 감소시키기위해 시각적 하중 방법을 사용하였으며 0.8 bpp이하의 전송율에서 인간의 시각 특성에 만족되는 변환부호화를 시험하였다.

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수지표고지형의 정확도 향상을 위한 지형의 분류와 보간법의 상용에 관한 연구 (A Study on the Application of Interpolation and Terrain Classification for Accuracy Improvement of Digital Elevation Model)

  • 문두열
    • 한국해양공학회지
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    • 제8권2호
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    • pp.64-79
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    • 1994
  • In this study, terrain classification, which was done by using the quantitative classification parameters and suitable interpolation method was applied to improve the accuracy of digital elevation models, and to increase its practical use of aerial photogrammetry. A terrain area was classified into three groups using the quantitative classification parameters to the ratio of horizontal, inclined area, magnitude of harmonic vectors, deviation of vector, the number of breakline and proposed the suitable interpolation. Also, the accuracy of digital elevation models was improved in case of large grid intervals by applying combined interpolation suitable for each terrain group. As a result of this study, I have an algorithm to perform the classification of the topography in the area of interest objectively and decided optimal data interpolation scheme for given topography.

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