• 제목/요약/키워드: predicting demand

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광어 생산량 예측을 위한 회귀분석 자동화 시스템 구축 (Automation of Regression Analysis for Predicting Flatfish Production)

  • 안진현;강정운;김민철;박소영
    • 한국정보통신학회:학술대회논문집
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    • 한국정보통신학회 2021년도 추계학술대회
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    • pp.128-130
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    • 2021
  • 본 연구는 광어의 적정 생산량 예측을 위한 회귀분석 자동화 시스템 구축을 목표로 한다. 현재 우리나라의 세계 각국과 FTA 체결 및 시장 개방 가속화 등으로 인해 한국 광어 양식 사업들은 환경의 특수성과 불확실성에 의해 많은 어려움을 겪고 있다. 또한 최근 연어, 방어 등의 수입 수산물의 급증과 국민들의 식생활 변화로 소비 부진 및 가격 하락 등의 문제를 해결할 방안이 필요한 실정이다. 이에 본 연구에서는 양식 광어의 수급 안정과 경제적 가치를 분석하여 적정한 광어 생산량을 알기 위해 빅 데이터를 활용한 회귀분석 자동화 시스템을 구현하였으며, 파이썬 모듈인 xlwings를 활용하여 광어의 생산금액과 생산량에 대한 가중치를 구하고 추후 생산될 광어의 양을 예측하는 데 활용하였다. 따라서 이러한 광어 생산량 예측에 대한 분석 결과를 토대로 향후 광어 양식 업계에서는 적정 생산량 달성 및 수급 조절 방안을 마련할 수 있을 것이며, 이는 불필요한 경제적 손실을 줄이고 데이터를 기반한 새로운 가치창출을 도모할 수 있을 것이다. 또한 본 연구에서 시도한 데이터 접근 방식을 통해 향후 여러 분야의 연구에서는 인공신경망, 다중회귀분석 등 다양한 분석 기법을 활용할 수 있고 이는 다양한 업계에서 효과적으로 빅데이터를 분석하고 활용할 수 있는 기초적인 자료의 토대가 될 것이다.

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Transverse seismic response of continuous steel-concrete composite bridges exhibiting dual load path

  • Tubaldi, E.;Barbato, M.;Dall'Asta, A.
    • Earthquakes and Structures
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    • 제1권1호
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    • pp.21-41
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    • 2010
  • Multi-span steel-concrete composite (SCC) bridges are very sensitive to earthquake loading. Extensive damage may occur not only in the substructures (piers), which are expected to yield, but also in the other components (e.g., deck, abutments) involved in carrying the seismic loads. Current seismic codes allow the design of regular bridges by means of linear elastic analysis based on inelastic design spectra. In bridges with superstructure transverse motion restrained at the abutments, a dual load path behavior is observed. The sequential yielding of the piers can lead to a substantial change in the stiffness distribution. Thus, force distributions and displacement demand can significantly differ from linear elastic analysis predictions. The objectives of this study are assessing the influence of piers-deck stiffness ratio and of soil-structure interaction effects on the seismic behavior of continuous SCC bridges with dual load path, and evaluating the suitability of linear elastic analysis in predicting the actual seismic behavior of these bridges. Parametric analysis results are presented and discussed for a common bridge typology. The response dependence on the parameters is studied by nonlinear multi-record incremental dynamic analysis (IDA). Comparisons are made with linear time history analysis results. The results presented suggest that simplified linear elastic analysis based on inelastic design spectra could produce very inaccurate estimates of the structural behavior of SCC bridges with dual load path.

기계학습을 이용한 태양광 발전량 예측 및 결함 검출 시스템 개발 (Development of a System for Predicting Photovoltaic Power Generation and Detecting Defects Using Machine Learning)

  • 이승민;이우진
    • 정보처리학회논문지:컴퓨터 및 통신 시스템
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    • 제5권10호
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    • pp.353-360
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    • 2016
  • 여러 개의 태양전지들이 붙어 있는 태양광 패널을 이용하여 전력을 생산하는 태양광 발전은 최근 신재생 에너지 기술로 빠르게 성장하고 있는 분야이다. 하지만 태양광발전의 단점 중 하나인 불규칙한 전력 생산문제로 인해, 장비 및 패널 결함에 빠르게 대응하지 못하는 문제가 발생한다. 이 연구에서는 다양한 기후데이터와 패널 정보를 이용하여 태양광발전량 예측 방법들을 비교하여 최적의 예측 알고리즘을 평가하고 이를 기반으로 태양광발전소 결함 검출 시스템을 개발하여 국내 태양광 발전소에 적용한 사례를 기술한다.

A Study on the Influence of a Sewage Treatment Plant's Operational Parameters using the Multiple Regression Analysis Model

  • Lee, Seung-Pil;Min, Sang-Yun;Kim, Jin-Sik;Park, Jong-Un;Kim, Man-Soo
    • Environmental Engineering Research
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    • 제19권1호
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    • pp.31-36
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    • 2014
  • In this study, the influence of the control and operational parameters within a sewage treatment plant were reviewed by performing multiple regression analysis on the effluent quality of the sewage treatment. The data used for this review are based on the actual data from a sewage treatment plant using the media process within the year 2012. The prediction models of chemical oxygen demand ($COD_{Mn}$) and total nitrogen (T-N) within the effluent of the 2nd settling tank based on the multiple regression analysis yielded the prediction accuracy measurements of 0.93 and 0.84, respectively; and it was concluded that the model was accurately predicting the variances of the actual observed values. If the data on the energy spent on each operating condition can be collected, then the operating parameter that conserves energy without violating the effluent quality standards of COD and T-N can be determined using the regression model and the standardized regression coefficients. These results can provide appropriate operation guidelines to conserve energy to the operators at sewage treatment plants that consume a lot of energy.

기계학습 알고리즘을 활용한 지역 별 아파트 실거래가격지수 예측모델 비교: LIME 해석력 검증 (Comparative Analysis for Real-Estate Price Index Prediction Models using Machine Learning Algorithms: LIME's Interpretability Evaluation)

  • 조보근;박경배;하성호
    • 한국정보시스템학회지:정보시스템연구
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    • 제29권3호
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    • pp.119-144
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    • 2020
  • Purpose Real estate usually takes charge of the highest proportion of physical properties which individual, organizations, and government hold and instability of real estate market affects the economic condition seriously for each economic subject. Consequently, practices for predicting the real estate market have attention for various reasons, such as financial investment, administrative convenience, and wealth management. Additionally, development of machine learning algorithms and computing hardware enhances the expectation for more precise and useful prediction models in real estate market. Design/methodology/approach In response to the demand, this paper aims to provide a framework for forecasting the real estate market with machine learning algorithms. The framework consists of demonstrating the prediction efficiency of each machine learning algorithm, interpreting the interior feature effects of prediction model with a state-of-art algorithm, LIME(Local Interpretable Model-agnostic Explanation), and comparing the results in different cities. Findings This research could not only enhance the academic base for information system and real estate fields, but also resolve information asymmetry on real estate market among economic subjects. This research revealed that macroeconomic indicators, real estate-related indicators, and Google Trends search indexes can predict real-estate prices quite well.

Uni-axial behaviour of normal-strength concrete-filled-steel-tube columns with external confinement

  • Ho, J.C.M.;Luo, L.
    • Earthquakes and Structures
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    • 제3권6호
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    • pp.889-910
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    • 2012
  • Because of the heavy demand of confining steel to restore the column ductility in seismic regions, it is more efficient to confine these columns by hollow steel tube to form concrete-filled-steel-tube (CFST) column. Compared with transverse reinforcing steel, steel tube provides a stronger and more uniform confining pressure to the concrete core, and reduces the steel congestion problem for better concrete placing quality. However, a major shortcoming of CFST columns is the imperfect steel-concrete interface bonding occurred at the elastic stage as steel dilates more than concrete in compression. This adversely affects the confining effect and decrease the elastic modulus. To resolve the problem, it is proposed in this study to use external steel confinement in the forms of rings and ties to restrict the dilation of steel tube. For verification, a series of uni-axial compression test was performed on some CFST columns with external steel rings and ties. From the results, it was found that: (1) Both rings and ties improved the stiffness of the CFST columns and (2) the rings improve significantly the axial strength of the CFST columns while the ties did not improve the axial strength. Lastly, a theoretical model for predicting the axial strength of confined CFST columns will be developed.

A Prediction of Nutrition Water for Strawberry Production using Linear Regression

  • Venkatesan, Saravanakumar;Sathishkumar, VE;Park, Jangwoo;Shin, Changsun;Cho, Yongyun
    • International journal of advanced smart convergence
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    • 제9권1호
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    • pp.132-140
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    • 2020
  • It is very important to use appropriate nutrition water for crop growth in hydroponic farming facilities. However, in many cases, the supply of nutrition water is not designed with a precise plan, but is performed in a conventional manner. We proposes a forecasting technique for nutrition water requirements based on a data analysis for optimal strawberry production. To do this, the proposed forecasting technique uses linear regression for correlating strawberry production, soil condition, and environmental parameters with nutrition water demand for the actual two-stage strawberry production soil. Also, it includes predicting the optimal amount of nutrition water requires according to the heterogeneous cultivation environment and variety by comparing the amount of nutrition water needed for the growth and production of different kinds of strawberries. We suggested study uses two types of section beds that are compared to find out the best section bed production of strawberry growth. The dataset includes 233 samples collected from a real strawberry greenhouse, and the four predicted variables consist of the total amounts of nutrition water, average temperature, humidity, and CO2 in the greenhouse.

Nonlinear seismic analysis of a super 13-element reinforced concrete beam-column joint model

  • Adom-Asamoah, Mark;Banahene, Jack Osei
    • Earthquakes and Structures
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    • 제11권5호
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    • pp.905-924
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    • 2016
  • Several two-dimensional analytical beam column joint models with varying complexities have been proposed in quantifying joint flexibility during seismic vulnerability assessment of non-ductile reinforced concrete (RC) frames. Notable models are the single component rotational spring element and the super element joint model that can effectively capture the governing inelastic mechanisms under severe ground motions. Even though both models have been extensively calibrated and verified using quasi-static test of joint sub-assemblages, a comparative study of the inelastic seismic responses under nonlinear time history analysis (NTHA) of RC frames has not been thoroughly evaluated. This study employs three hypothetical case study RC frames subjected to increasing ground motion intensities to study their inherent variations. Results indicate that the super element joint model overestimates the transient drift ratio at the first story and becomes highly un-conservative by under-predicting the drift ratios at the roof level when compared to the single-component model and the conventional rigid joint assumption. In addition, between these story levels, a decline in the drift ratios is observed as the story level increased. However, from this limited study, there is no consistent evidence to suggest that care should be taken in selecting either a single or multi component joint model for seismic risk assessment of buildings when a global demand measure such as maximum inter-storey drift is employed in the seismic assessment framework.

An Evaluation for Predicting the Far Wake of Tidal Turbines

  • 양창조;황안둥
    • 한국마린엔지니어링학회:학술대회논문집
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    • 한국마린엔지니어링학회 2012년도 전기공동학술대회 논문집
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    • pp.155-156
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    • 2012
  • In the modern age, as man's demand of energy is continuously grew, tidal becomes one of the sustainable energy sources that have been investigating thoroughly recently. Tidal turbine has proved high potential as a future power-generating device. To effectively capture tidal energy on site, a group of tidal turbines should be used and positioned in some formation with proper size and space so that energy can be absorbed from multiple point. Thus, the turbines together with the flow filed becomes a huge domain, a tidal farm. So, it becomes more convenient if a whole turbine farm is simulated by means of actuator discs since the time and cost for analysis can be reduced. This paper aims to evaluate the operating performance (power efficiency and energy restoration rate), mutual influence (for different longitudinal and lateral spaces), the influence of velocity profiles, turbulence intensity and the far wake characteristic of tidal turbines operating in farm formation. The results of this study help contributing to the present development of tidal turbine as the future potential energy conversion machinery.

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Movie Recommendation System Based on Users' Personal Information and Movies Rated Using the Method of k-Clique and Normalized Discounted Cumulative Gain

  • Vilakone, Phonexay;Xinchang, Khamphaphone;Park, Doo-Soon
    • Journal of Information Processing Systems
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    • 제16권2호
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    • pp.494-507
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    • 2020
  • This study proposed the movie recommendation system based on the user's personal information and movies rated using the method of k-clique and normalized discounted cumulative gain. The main idea is to solve the problem of cold-start and to increase the accuracy in the recommendation system further instead of using the basic technique that is commonly based on the behavior information of the users or based on the best-selling product. The personal information of the users and their relationship in the social network will divide into the various community with the help of the k-clique method. Later, the ranking measure method that is widely used in the searching engine will be used to check the top ranking movie and then recommend it to the new users. We strongly believe that this idea will prove to be significant and meaningful in predicting demand for new users. Ultimately, the result of the experiment in this paper serves as a guarantee that the proposed method offers substantial finding in raw data sets by increasing accuracy to 87.28% compared to the three most successful methods used in this experiment, and that it can solve the problem of cold-start.