• 제목/요약/키워드: statistical bias indicators

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Statistical bias indicators for the long-term displacement of steel-concrete composite beams

  • Moreno, Julian A.;Tamayo, Jorge L.P.;Morsch, Inacio B.;Miranda, Marcela P.;Reginato, Lucas H.
    • Computers and Concrete
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    • 제24권4호
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    • pp.379-397
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    • 2019
  • Steel-concrete composite beams are widely employed in constructions and their performance at the serviceability stage is of concern among practitioners and design regulations. In this context, an accurate evaluation of long-term deflections via various rheological concrete models is needed. In this work, the performance and predict capability of some concrete creep and shrinkage models ACI, CEB, B3, FIB and GL2000 are ascertained, and compared by using statistical bias indicators. Ten steel-concrete composite beams with existing experimental and numerical results are then modeled for this purpose. The proposed modeling technique uses the finite element method, where the concrete slab and steel beam are modeled with shell finite elements. Concrete is considered as an aging viscoelastic material and cracking is treated with the common smeared approach. The results show that when the experimental ultimate shrinkage strain is used for calibration, all studied rheological models predict nearly similar deflections, which agree with the experimental data. In contrast, significance differences are encountered for some models, when none calibration is made prior to. A value between twenty and thirty times the cracking strain is recommended for the ultimate tensile strain in the tension stiffening model. Also, increasing the relative humidity and decreasing the ambient temperature can lead to a substantial reduction of slab cracking for beams under negative flexure. Finally, there is not a unique rheological model that clearly excels in all scenarios.

Application of Convolutional Neural Networks (CNN) for Bias Correction of Satellite Precipitation Products (SPPs) in the Amazon River Basin

  • Alena Gonzalez Bevacqua;Xuan-Hien Le;Giha Lee
    • 한국수자원학회:학술대회논문집
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    • 한국수자원학회 2023년도 학술발표회
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    • pp.159-159
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    • 2023
  • The Amazon River basin is one of the largest basins in the world, and its ecosystem is vital for biodiversity, hydrology, and climate regulation. Thus, understanding the hydrometeorological process is essential to the maintenance of the Amazon River basin. However, it is still tricky to monitor the Amazon River basin because of its size and the low density of the monitoring gauge network. To solve those issues, remote sensing products have been largely used. Yet, those products have some limitations. Therefore, this study aims to do bias corrections to improve the accuracy of Satellite Precipitation Products (SPPs) in the Amazon River basin. We use 331 rainfall stations for the observed data and two daily satellite precipitation gridded datasets (CHIRPS, TRMM). Due to the limitation of the observed data, the period of analysis was set from 1st January 1990 to 31st December 2010. The observed data were interpolated to have the same resolution as the SPPs data using the IDW method. For bias correction, we use convolution neural networks (CNN) combined with an autoencoder architecture (ConvAE). To evaluate the bias correction performance, we used some statistical indicators such as NSE, RMSE, and MAD. Hence, those results can increase the quality of precipitation data in the Amazon River basin, improving its monitoring and management.

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환경보건지표를 이용한 지역 환경보건수준 평가 사례연구 (A Case Study on the Evaluation of Environmental Health Status based on Environmental Health Indicators)

  • 정순원;이영미;홍성준;장준영;유승도;최경희;박충희
    • 한국환경보건학회지
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    • 제42권5호
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    • pp.302-313
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    • 2016
  • Objectives: This study was conducted to assess environmental health status on a local scale using environmental health-related indicators. It demonstrated the possibility of using a structural equation model, a methodological approach to provide synthesized information. Methods: Eighteen indicators were selected from official statistical data published by local governments. Each environmental health-related indicator was classified according to the PSR (pressure-state-response) model. Aggregation methods were performed using principal component analysis and fuzzy sets. Results: The five principal components were classified through principal component analysis (PCA) and obtained eigenvalues >1.0 from the initial 18 indicators. The aggregated index was obtained by condensing the original information into two broad and simple categories through fuzzy sets. Conclusion: This could be useful in that the aggregation procedure may provide a basis for establishing environmental health policies and a decision-making process. However, the availability and quality of indicators, assessment of aggregation method bias, choice of weighted scores for indicators, and other factors should be examined in future studies.

Predictive Modeling of the Growth and Survival of Listeria monocytogenes Using a Response Surface Model

  • Jin, Sung-Sik;Jin, Yong-Guo;Yoon, Ki-Sun;Woo, Gun-Jo;Hwang, In-Gyun;Bahk, Gyung-Jin;Oh, Deog-Hwan
    • Food Science and Biotechnology
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    • 제15권5호
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    • pp.715-720
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    • 2006
  • This study was performed to develop a predictive model for the growth kinetics of Listeria monocytogenes in tryptic soy broth (TSB) using a response surface model with a combination of potassium lactate (PL), temperature, and pH. The growth parameters, specific growth rate (SGR), and lag time (LT) were obtained by fitting the data into the Gompertz equation and showed high fitness with a correlation coefficient of $R^2{\geq}0.9192$. The polynomial model was identified as an appropriate secondary model for SGR and LT based on the coefficient of determination for the developed model ($R^2\;=\;0.97$ for SGR and $R^2\;=\;0.86$ for LT). The induced values that were calculated using the developed secondary model indicated that the growth kinetics of L. monocytogenes were dependent on storage temperature, pH, and PL. Finally, the predicted model was validated using statistical indicators, such as coefficient of determination, mean square error, bias factor, and accuracy factor. Validation of the model demonstrates that the overall prediction agreed well with the observed data. However, the model developed for SGR showed better predictive ability than the model developed for LT, which can be seen from its statistical validation indices, with the exception of the bias factor ($B_f$ was 0.6 for SGR and 0.97 for LT).

Herding Behavior Model in Investment Decision on Emerging Markets: Experimental in Indonesia

  • RAHAYU, Sri;ROHMAN, Abdul;HARTO, Puji
    • The Journal of Asian Finance, Economics and Business
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    • 제8권1호
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    • pp.53-59
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    • 2021
  • This research aims to examine the model of investor herding behavior in making investment decisions in the Indonesian capital market, which is influenced by social and information impacting on the value of the Book Value Per Share (BVPS). The latest stock market conditions show that most investors make the same error pattern in making investment decisions that result in losses. The experiment involves two independent variables, namely, information about BVPS and social influence. This study used a 2×2 factorial design laboratory experimental method. Data collection was carried out through treatment of a sample of 100 individual investors listed on the Indonesia Stock Exchange. Univariate Two-Way Analysis of Variance (ANOVA) statistical tool was used to test the independent variable on the dependent variable. Research results showed that the social influence originating from expert investors is more influential than the Book Value Per Share (BVPS) information on the behavior of herding investors in making investment decisions. These findings suggest that investors know their psychological factors, thereby increasing self-control and investment analysis skills. Further research can use psychological bias and other indicators of accounting relevant information such as Earning Per Share (EPS) to test herding behavior in investment decision making in the capital market.

교육용 웹 사이트 평가를 위한 준거의 개발 및 적용 (Development and Application of Criteria for Evaluating Educational Web Sites)

  • 김미량
    • 컴퓨터교육학회논문지
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    • 제6권1호
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    • pp.41-54
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    • 2003
  • 웹에 존재하는 넘치는 정보 중에서 이를 교육의 목적으로 활용하기 위해서는 해당 정보에 대한 사전 검증이 반드시 선행되어야 한다. 현재에도 웹의 많은 정보들이 교수-학습의 내용으로 활용되고 있고 또 웹기반교육이나 정보통신기술활용교육의 소재가 되고 있으나 이들 정보에 대한 총체적 질을 관리하기란 여간 어려운 일이 아니다. 본 연구는 교육용 웹 사이트에서 제공하는 정보의 질 관리에 유용한 도움을 줄 수 있는 평가의 준거를 개발, 적용해 보고 이러한 과정을 통하여 교육용 웹 사이트 설계, 개발과정에 최우선적으로 고려되어야 할 중요한 사항들을 제안해 보고자 하였다. 이를 위해, 교육용 웹 사이트의 평가에 유용하다고 판단되는 평가항목들을 체계적으로 분류 정리하고 교육용 웹 사이트에 대한 만족도 항목을 추가한 뒤, 통계적 분석과정을 통해 의미있는 평가준거들을 제안하였다. 각 개별 평가항목을 설문항목으로 전환하여 설문조사를 실시하여 개별항목의 신뢰성과 타당성을 검증해 보았으며 이 과정을 통해 추출된 14개 요인과 웹 사이트 만족도 간의 희귀분석을 통해 중요 평가지표들을 추출해 보았다. 이 과정에서 학습자중심의 교육용 웹 사이트 개발에 최우선적으로 고려되어야 할 평가지표들이 제안 되었고, 설계적 시사점 등이 논의되었다.

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Sequence to Sequence based LSTM (LSTM-s2s)모형을 이용한 댐유입량 예측에 대한 연구 (Application of sequence to sequence learning based LSTM model (LSTM-s2s) for forecasting dam inflow)

  • 한희찬;최창현;정재원;김형수
    • 한국수자원학회논문집
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    • 제54권3호
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    • pp.157-166
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    • 2021
  • 효율적인 댐 운영을 위해서는 높은 신뢰도를 기반으로 하는 유입량 예측이 요구된다. 본 연구에서는 최근 다양한 분야에서 사용되고 있는 데이터 기반의 예측 방법 중 하나인 딥러닝을 댐 유입량 예측에 활용하였다. 그 중 시계열 자료 예측에 높은 성능을 보이는 Sequence-to-Sequence 구조기반의 Long Short-Term Memory 딥러닝 모형(LSTM-s2s)을 이용하여 소양강 댐의 유입량을 예측하였다. 모형의 예측 성능을 평가하기 위해 상관계수, Nash-Sutcliffe 효율계수, 평균편차비율, 그리고 첨두값 오차를 이용하였다. 그 결과, LSTM-s2s 모형은 댐 유입량 예측에 대한 높은 정확도를 보였으며, 단일 유량 수문곡선 기반의 예측 성능에서도 높은 신뢰도를 보였다. 이를 통해 홍수기와 이수기에 수자원 관리를 위한 효율적인 댐 운영에 딥러닝 모형의 적용 가능성을 확인할 수 있었다.

Reassessment of viscoelastic response in steel-concrete composite beams

  • Miranda, Marcela P.;Tamayo, Jorge L.P.;Morsch, Inacio B.
    • Structural Engineering and Mechanics
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    • 제81권5호
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    • pp.617-631
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    • 2022
  • In this paper the viscoelastic responses of four experimental steel-concrete composite beams subjected to highly variable environmental conditions are investigated by means of a finite element (FE) model. Concrete specimens submitted to stepped stress changes are also evaluated to validate the current formulations. Here, two well-known approaches commonly used to solve the viscoelastic constitutive relationship for concrete are employed. The first approach directly solves the integral-type form of the constitutive equation at the macroscopic level, in which aging is included by updating material properties. The second approach is postulated from a rate-type law based on an age-independent Generalized Kelvin rheological model together with Solidification Theory, using a micromechanical based approach. Thus, conceptually both approaches include concrete hardening in two different manners. The aim of this work is to compare and analyze the numerical prediction in terms of long-term deflections of the studied specimens according to both approaches. To accomplish this goal, the performance of several well-known model codes for concrete creep and shrinkage such as ACI 209, CEB-MC90, CEB-MC99, B3, GL 2000 and FIB-2010 are evaluated by means of statistical bias indicators. It is shown that both approaches with minor differences acceptably match the long-term experimental deflection and are able to capture complex oscillatory responses due to variable temperature and relative humidity. Nevertheless, the use of an age-independent scheme as proposed by Solidification Theory may be computationally more advantageous.

편견과 환경요인이 창업 의지에 미치는 영향에 관한 연구: 실패두려움의 매개효과 (A Study on the Impact of Prejudice and Environmental Factors on Entrepreneurship Intention: Mediating Role of Fear of Failure)

  • 이지연;정찬구
    • 벤처창업연구
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    • 제18권5호
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    • pp.141-157
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    • 2023
  • 창업은 경제발전의 원동력이자 국가경쟁력 향상에 중요한 역할임에 나라의 창업지원정책은 매년 늘어나고 있지만 이에 도전하지 않고 향후 창업을 고려하지 않는다는 지표는 고용축소를 예측할 수 있고 실업이 더욱더 증가할 수 있다고 볼 수 있다. 아무것도 하지 않는 청년층의 증가는 경제적 고통과 미래의 소중한 인력의 방치로 국가적으로 보다 현실적인 창업정책이 요구되는 상황이다. 이에 본 연구에서는 우리나라 잠재적 창업자의 창업의지에 영향을 미치는 요인을 밝히고자, 편견과 환경적 요인에 대하여 규명하고자 하였다. 이를 위해 창업에 관심이 있는 잠재적 창업가인 일반인을 대상으로 227부의 응답을 표본으로 SPSS.25를 이용하여 기술통계분석을 실행하였다. 그 결과 편견은 창업의지를 감소시키고, 실패두려움을 증가시켰다. 반면에 창업자의 환경요인은 실패두려움을 감소시키고, 창업의지는 증가시켰다. 마지막으로 실패두려움은 두 독립변수와 창업의지 간에 부분 매개역할을 하는 것으로 나타났다. 본 연구 결과를 볼 때 편견은 창업의지에 부정적인 요소이고 환경은 긍정적요인으로 나타났다. 이러한 연구 결과는 창업 활성화를 위하여 창업에 대한 창업가의 올바른 인식과 지지받을 수 있는 긍정적인 환경요인이 필요함을 시사하고 있다.

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중국이동통신산업중적복무질량(中国移动通信产业中的服务质量), 고객만의도화고객충성도(顾客满意度和顾客忠诚度) (Service Quality, Customer Satisfaction and Customer Loyalty of Mobile Communication Industry in China)

  • Zhang, Ruijin;Li, Xiangyang;Zhang, Yunchang
    • 마케팅과학연구
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    • 제20권3호
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    • pp.269-277
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    • 2010
  • 现有文献表明, 影响服务业顾客忠诚的最重要因素是服务质量. 然而, 在服务质量是直接还是间接影响顾客忠诚方面, 学者们的观点有着明显的分歧. 目前, 中国国内专门针对移动通信行业服务质量与顾客忠诚之间关系的文章较少. 此外, 以往相关文献多是将顾客忠诚作为一个整体变量进行研究, 没有进一步将其细分为多个维度. 基于此, 本文拟通过实证研究来探析移动通信业服务质量各维度与顾客忠诚各维度之间的直接和间接影响机理, 其中选择顾客满意作为二者关系的中介变量, 希望研究结论能给国内移动通信企业的服务管理提供有效的理论指导. 为了使搜集到的数据有效, 本次调研范围仅限于黑龙江哈尔滨市, 调查对象为移动通信公司的用户. 本次调研采取随机抽样的方式, 共发放问卷350份, 收回问卷325份, 回收率为 92.9%. 剔除无效问卷, 有效问卷为289份, 即有效回收率为82.6%. 本文借鉴国内外现有文献所使用的量表, 这些量表已经在实证研究中得到验证. 本文提出六个假设, 总体而言, 只有四个假设没有得到支持. 为了验证服务质量构成要素量表的合理性, 本文对289份有效样本进行探索性因子分析. 同样, 对顾客忠诚的维度进行检验. 本研究采用Cronbach's ${\alpha}$系数来评价量表的信度. 本研究从内容效度, 结构效度和聚合效度三方面对问卷进行效度检验. 本研究对数据和模型的拟合优度进行检验, 以提高假设检验的准确程度. 通过文献资料的收集, 整理及数据处理, 本文提出了服务质量五维度模型以及服务质量与顾客忠诚度之间相互关系模型, 通过实证分析验证了有形性, 可靠性, 反应性, 保证性和关怀性是服务质量的五个构成要素, 验证了PZB对于服务质量的SERVQUAL的测量方法, 研究了移动通信服务质量各维度对顾客忠诚各维度的直接影响机理, 以及服务质量各维度如何通过顾客满意这一中介变量对顾客忠诚各维度的间接影响机理, 建立了相应的关系模型,并运用结构方程分析方法,对模型进行实证检验, 得出如下研究结论: 第一, 移动通信服务质量由有形性, 可靠性, 响应性, 保证性和移情性五个要素构成, 顾客忠诚由态度忠诚和行为忠诚两个维度构成. 在PZB设计的SERVQUAL量表基础上, 本文针对移动通信行业设计了服务质量测量量表, 通过探索性因子分析得出五个因子. 这五个因子与五构成要素基本一致, 说明服务质量五要素概念适用于移动通信行业. 同样, 对顾客忠诚量表进行因子分析, 得出两个因子, 与本文中的态度忠诚和行为忠诚相一致. 第二, 移动通信服务质量对顾客忠诚存在直接和间接的正向影响作用. 其中, 服务质量对态度忠诚有直接和间接的正向作用, 间接作用是通过顾客满意这一中介变量影响的; 服务质量对行为忠诚有直接和间接的正向作用, 间接作用是通过顾客满意和态度忠诚这两个中介变量影响的. 这说明移动通信服务质量越好, 顾客的满意度越高, 其对服务提供商的态度就越积极, 在行为上就越容易表现出对服务提供商的忠诚. 而且, 服务质量各维度对顾客忠诚各维度的影响机理是不同的, 比如: 有形性对顾客满意有直接的正向作用, 但对顾客忠诚却没有显著的直接作用; 保证性对顾客满意没有显著的直接作用, 但对顾客忠诚有直接和间接的正向作用. 第三, 顾客满意在移动通信服务质量与态度忠诚, 行为忠诚之间的具有显著的中介作用, 这说明服务质量的提高可以增加顾客的满意度, 而满意的顾客更容易成为忠诚的顾客; 而态度忠诚在移动通信服务质量与行为忠诚之间的具有显著的中介作用, 这说明顾客行为上表现出忠诚可能是虚假忠诚, 只有态度和行为都忠诚的顾客才是真正的忠诚顾客. 本文的研究结论对中国及其它国家的电信运营商如何提升服务质量有一定的借鉴意义. 本文存在两方面的局限性: 首先, 本研究仅在黑龙江哈尔滨地区进行问卷调研, 针对移动公司用户, 统计数据会存在一定的抽样误差, 影响最终的统计分析结果. 第二, 本研究主要探讨了服务质量对顾客忠诚的影响关系, 并引入了顾客满意作为中介变量, 但没有考虑其他可能影响顾客忠诚的因素, 例如顾客价值, 消费者特征等.