• 제목/요약/키워드: Accumulated Data

검색결과 1,414건 처리시간 0.034초

머신러닝을 이용한 국내 수입 자동차 구매 해약 예측 모델 연구: H 수입차 딜러사 대상으로 (A Study on the Prediction Model for Imported Vehicle Purchase Cancellation Using Machine Learning: Case of H Imported Vehicle Dealers)

  • 정동균;이종화;이현규
    • 한국정보시스템학회지:정보시스템연구
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    • 제30권2호
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    • pp.105-126
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    • 2021
  • Purpose The purpose of this study is to implement a optimal machine learning model about the cancellation prediction performance in car sales business. It is to apply the data set of accumulated contract, cancellation, and sales information in sales support system(SFA) which is commonly used for sales, customers and inventory management by imported car dealers, to several machine learning models and predict performance of cancellation. Design/methodology/approach This study extracts 29,073 contracts, cancellations, and sales data from 2015 to 2020 accumulated in the sales support system(SFA) for imported car dealers and uses the analysis program Python Jupiter notebook in order to perform data pre-processing, verification, and modeling that is applying and learning to Machine learning model after then the final result was predicted using new data. Findings This study confirmed that cancellation prediction is possible by applying car purchase contract information to machine learning models. It proved the possibility of developing and utilizing a generalized predictive model by using data of imported car sales system with machine learning technology. It can reduce and prevent the sales failure as caring the potential lost customer intensively and it lead to increase sales revenue by predicting the cancellation possibility of individual customers.

A Study on the Application of Measurement Data Using Machine Learning Regression Models

  • Yun-Seok Seo;Young-Gon Kim
    • International journal of advanced smart convergence
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    • 제12권2호
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    • pp.47-55
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    • 2023
  • The automotive industry is undergoing a paradigm shift due to the convergence of IT and rapid digital transformation. Various components, including embedded structures and systems with complex architectures that incorporate IC semiconductors, are being integrated and modularized. As a result, there has been a significant increase in vehicle defects, raising expectations for the quality of automotive parts. As more and more data is being accumulated, there is an active effort to go beyond traditional reliability analysis methods and apply machine learning models based on the accumulated big data. However, there are still not many cases where machine learning is used in product development to identify factors of defects in performance and durability of products and incorporate feedback into the design to improve product quality. In this paper, we applied a prediction algorithm to the defects of automotive door devices equipped with automatic responsive sensors, which are commonly installed in recent electric and hydrogen vehicles. To do so, we selected test items, built a measurement emulation system for data acquisition, and conducted comparative evaluations by applying different machine learning algorithms to the measured data. The results in terms of R2 score were as follows: Ordinary multiple regression 0.96, Ridge regression 0.95, Lasso regression 0.89, Elastic regression 0.91.

변압기 온라인 예방진단 센서의 점검현황 (Inspection On Sensors of Online Preventive diagnostic system Sensors for Power Transformer)

  • 구교선;권동진;진상범;곽주식;강연욱
    • 한국조명전기설비학회:학술대회논문집
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    • 한국조명전기설비학회 2005년도 춘계학술대회논문집
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    • pp.455-460
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    • 2005
  • Preventive diagnostic system for power transformer prevents the sudden power failure through monitoring of abnormal symptoms. KEPCO has adopted the preventive diagnostic system at nine 345kV substations since 1997. Application techniques of the diagnostic sensors were settled, but diagnostic algorithm and practical use of accumulated data are not yet established. To build up the diagnostic algorithm and effective use of the preventive diagnostic system, the reliability of the data accumulated in a server computer is very important. Therefore, this paper describes problem when apply system to substation and solution way to improve reliability of the system

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실적자료분석(實績資料分析)에 의(依)한 일정계획(日程計劃) (A Work Scheduling Based on Analysis of Performance Data)

  • 김동찬;김우식
    • 대한산업공학회지
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    • 제4권2호
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    • pp.59-66
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    • 1978
  • This paper is a work scheduling for design of piping Department of chemical plant using accumulated curve. Accumulated curve prepared by analysis of performance data, collected executed manhours for chemical plant of "D" Company during the past two years. It compared scheduled manhours with actual used manhours up to six months, put into the form of figures and charts the results can he summarized as below; 1) It can he found an important factor of critical control thus piping department got 30% of total scheduled menhours. 2) A plan of manpower mobilization can be scheduled before work starting. 3) Project progress can he found easily as put into the form of figures and charts for schedule to actual.

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전력용 변압기 예방진단 기준치 검토 (Investigation of the Preventive Diagnostic Criteria for Power Transformer)

  • 권동진;구교선;강연욱;우정욱;곽주식
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2005년도 제36회 하계학술대회 논문집 A
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    • pp.592-596
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    • 2005
  • The preventive diagnostic system prevents transformers from power failure by giving alarm and observing transformers in service. And it helps to establish the plan for optimum maintenance of transformer as well as to find location or cause of fault using accumulated data. KEPCO has adopted the preventive diagnostic system at nine 345kV substations since 1997. Techniques for component sensors of preventive diagnostic system were settled but diagnostic algorithm, diagnostic criteria and practical use of accumulated data are not yet established. This paper, to build up the base of preventive diagnostic algorithm for the power transformer, investigated the preventive diagnostic criteria for power transformer.

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현장 관측 자료를 이용한 금오산 계명대학교 동영학술림 부근의 생물기후환경 분석 (Analysis of Bioclimatic Variables in Mt. Geumo Region Adjacent to Keimyung Dongyeong Forest )

  • 김하영;박수진;김해동
    • 한국환경과학회지
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    • 제32권5호
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    • pp.365-374
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    • 2023
  • Eight years (2014-2021) of climate data were collected from an automatic weather observation system installed at the foot of Mt. Geumo in Chilgok, Gyeongbuk. Using these data, we investigated local bio-climatological indices (warmth index, WI; coldness index, CI; and effective accumulated temperature, EAT) of the mountain region adjacent to the Keimyung Dongyeong forest. The study area's WI and CI were 109.3℃ and -11.3℃ per month, respectively, averaged across 8 years. These values are indicative of an evergreen broad-leaved forest in the warm temperate climate zone, suitable for cultivating sweet persimmons and figs. Additionally, EAT in Dongyeong was 2,113.7℃, averaged across 8 years, suitable for growing crops such as corn, soybean, and potato.

건설공사 사후평가결과보고서 표준화 방안 (Standardization for Post-Construction Evaluation Report)

  • 김경훈;이찬규
    • 한국건축시공학회:학술대회논문집
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    • 한국건축시공학회 2023년도 봄 학술논문 발표대회
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    • pp.289-290
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    • 2023
  • According to relevant laws, in the case of a construction project with a total construction cost of 30 billion won or more, a post-construction evaluation must be performed after completion. In addition, a post-construction evaluation report must be prepared and entered into the Continuous Acquisition & Life-cycle Support(CALS). As a result of reviewing the currently accumulated post-construction evaluation reports, since the report is not standardized, it is difficult for public project owners to write the report. It also hinders the post-construction evaluation and management center from verifying contents, analyzing data, and deriving meaningful results. In order to improve the convenience of the public owners who must conduct post-construction evaluations and the work efficiency of the center, evaluation factors were standardized and a standard post-construction evaluation report format for road construction was developed in Excel. Through this, the data in the reports will be effectively accumulated, managed, and analyzed, so that meaningful results will be produced and be helpful in future construction work.

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심리적 불안과 신체 수행도의 관계에 대한 연구 (A Study on Relation Between Psychological Anxiety and Physical Performance)

  • 조성훈;김태성;구일섭
    • 산업경영시스템학회지
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    • 제20권42호
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    • pp.151-159
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    • 1997
  • This Study intends to analyse the degree which Psychological Anxiety affects to Physical Performance using Multivariate Statistical Analysis. For this, we accumulated two type's datum : (1)Data about Psychological anxiety by Spielberger's STAI- Ⅰ·Ⅱ, (2)Data about Physical Performance by AEFH's FITKIT.

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전력용 변압기 예방진단새스템의 진단기준치 실정 (Establishment of Diagnostic Criteria in the Preventive Diagnostic System for the Power Transformer)

  • 권동진;구교선;곽주식;우정욱;강연욱
    • 대한전기학회논문지:전력기술부문A
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    • 제54권9호
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    • pp.449-456
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    • 2005
  • The preventive diagnostic technique prevents transformers from power failure through giving alarm and observing transformers in service. And it helps to establish the plan for optimum maintenance of the transformer as well as to find location or cause of fault using accumulated data. Data detection and experience of the preventive diagnostic system need to establish the preventive diagnostic algorithm regarding interrelationship between detected data and deterioration of equipment. Therefore in-depth analysis about the preventive diagnosis system is required. KEPCO has adopted the preventive diagnostic system at nine 345kV substations since 1997. Techniques for component sensors of the preventive diagnosis system were settled but diagnosis algorithm, diagnostic criteria and practical use of accumulated data are not yet established. This paper, to build up the base of preventive diagnostic algorithm for the Power transformer. investigated the preventive diagnostic criteria for the power transformer.

Smart-Walk 시스템에서 스트림 빅데이터 분석을 통한 최적화 기법 (An Optimization Technique for Smart-Walk Systems Using Big Stream Log Data)

  • 조완섭;양경은;이중엽
    • 한국산업정보학회논문지
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    • 제17권3호
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    • pp.105-114
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    • 2012
  • 본 논문에서는 장애인의 보행을 지원하는 Smart-Walk 시스템에서 하나의 시스템으로 여러 유형의 장애인을 지원할 수 있도록 하는 유니버설 디자인개념의 데이터베이스 구축방안을 제시한다. 또한, 운행로그를 분석하여 사용자의 사용현황과 이탈비율을 계산함으로써 시스템의 최적운영을 지원하는 방안을 제시한다. 다양한 사용자 유형과 그에 적합한 사용방법들을 데이터베이스에 저장하고 관리함으로써 간단하게 다양한 유형의 사용자들에게 지원할 수 있는 방법은 진정한 유니버설디자인 이념의 실현이라 할 수 있다. 사용자의 운행로그를 데이터웨어하우스 형태로 저장하고 온라인 분석 기법을 적용함으로써 시스템의 최적 운영에 유용한 정보를 실시간으로 추출해 낼 수 있게 된다.