• 제목/요약/키워드: Preprocessing-based

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Prediction of the price for stock index futures using integrated artificial intelligence techniques with categorical preprocessing

  • Kim, Kyoung-jae;Han, Ingoo
    • 한국경영과학회:학술대회논문집
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    • 한국경영과학회 1997년도 추계학술대회발표논문집; 홍익대학교, 서울; 1 Nov. 1997
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    • pp.105-108
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    • 1997
  • Previous studies in stock market predictions using artificial intelligence techniques such as artificial neural networks and case-based reasoning, have focused mainly on spot market prediction. Korea launched trading in index futures market (KOSPI 200) on May 3, 1996, then more people became attracted to this market. Thus, this research intends to predict the daily up/down fluctuant direction of the price for KOSPI 200 index futures to meet this recent surge of interest. The forecasting methodologies employed in this research are the integration of genetic algorithm and artificial neural network (GAANN) and the integration of genetic algorithm and case-based reasoning (GACBR). Genetic algorithm was mainly used to select relevant input variables. This study adopts the categorical data preprocessing based on expert's knowledge as well as traditional data preprocessing. The experimental results of each forecasting method with each data preprocessing method are compared and statistically tested. Artificial neural network and case-based reasoning methods with best performance are integrated. Out-of-the Model Integration and In-Model Integration are presented as the integration methodology. The research outcomes are as follows; First, genetic algorithms are useful and effective method to select input variables for Al techniques. Second, the results of the experiment with categorical data preprocessing significantly outperform that with traditional data preprocessing in forecasting up/down fluctuant direction of index futures price. Third, the integration of genetic algorithm and case-based reasoning (GACBR) outperforms the integration of genetic algorithm and artificial neural network (GAANN). Forth, the integration of genetic algorithm, case-based reasoning and artificial neural network (GAANN-GACBR, GACBRNN and GANNCBR) provide worse results than GACBR.

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라인스캔 카메라 인터페이스를 갖는 실시간 영상 전처리 시스템의 설계 (Design of a real-time image preprocessing system with linescan camera interface)

  • 류경;김경민;박귀태
    • 제어로봇시스템학회논문지
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    • 제3권6호
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    • pp.626-631
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    • 1997
  • This paper represents the design of a real-time image preprocessing system. The preprocessing system performs hardware-wise mask operations and thresholding operations at the speed of camera output single rate. The preprocessing system consists of the preprocessing board and the main processing board. The preprocessing board includes preprocessing unit that includes a $5\times5$ mask processor and LUT, and can perform mask and threshold operations in real-time. To achieve high-resolution image input data($20485\timesn$), the preprocessing board has a linescan camera interface. The main processing board includes the image processor unit and main processor unit. The image processor unit is equipped with TI's TMS320C32 DSP and can perform image processing algorithms at high speed. The main processor unit controls the operation of total system. The proposed system is faster than the conventional CPU based system.

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STATISTICALLY PREPROCESSED DATA BASED PARAMETRIC COST MODEL FOR BUILDING PROJECTS

  • Sae-Hyun Ji;Moonseo Park;Hyun-Soo Lee
    • 국제학술발표논문집
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    • The 3th International Conference on Construction Engineering and Project Management
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    • pp.417-424
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    • 2009
  • For a construction project to progress smoothly, effective cost estimation is vital, particularly in the conceptual and schematic design stages. In these early phases, despite the fact that initial estimates are highly sensitive to changes in project scope, owners require accurate forecasts which reflect their supplying information. Thus, cost estimators need effective estimation strategies. Practically, parametric cost estimates are the most commonly used method in these initial phases, which utilizes historical cost data (Karshenas 1984, Kirkham 2007). Hence, compilation of historical data regarding appropriate cost variance governing parameters is a prime requirement. However, precedent practice of data mining (data preprocessing) for denoising internal errors or abnormal values is needed before compilation. As an effort to deal with this issue, this research proposed a statistical methodology for data preprocessing and verified that data preprocessing has a positive impact on the enhancement of estimate accuracy and stability. Moreover, Statistically Preprocessed data Based Parametric (SPBP) cost models are developed based on multiple regression equations and verified their effectiveness compared with conventional cost models.

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컨테이너 터미널의 선처리 알고리즘 성능분석과 최적선택 제안 (Performance Analysis of Preprocessing Algorithm in Container Terminal and Suggestion for Optimum Selection)

  • 박영규
    • 유통과학연구
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    • 제16권12호
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    • pp.95-104
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    • 2018
  • Purpose - In order to gain the upper hand in competition between container terminals, efforts to improve container terminal productivity continue. Export containers arrive randomly in the container terminal and are carried in the container terminal yard according to the arrival order. On the other hand, containers are carried out of the container terminal yard in order based on container weight, not in order of arrival. Because the carry-in order and the carry-out order are different, rehandling may occur, which reduces the performance of the container terminals. In order to reduce rehandling number, containers can be moved in advance when they arrive, which is called preprocessing. This paper proposes an effective preprocessing algorithm and analyzes the factors that affect the productivity of the container terminals. It also provides a way to choose the best factors for preprocessing for a variety of situations. Research design, data, and methodology - To analyze the impact of factors affecting the performance of preprocessing algorithms presented in this paper, simulations are performed. The simulations are performed for two types of bays, 12 stacks with 8 tiers, and 8 stacks with 6 tiers. Results - The results of the factor analysis that affects the performance of the preprocessing algorithm were as follows. (1) As the LMF increased, preprocessing number increases and rehandling number decreased. (2) The LML effect was greatest when the LML changed from 0 to 1, and that the effect decreased when it changed above 1. (3) The sum of preprocessing number and rehandling number was then shown to be increased after decrease, as the LMF increased. (4) In the case of NCI, a decrease in NCI showed that the containers would become more grouped and thus the performance was improved. (5) There was a positive effect in the case of EFS. Conclusion - In this paper, preprocessing algorithm was proposed and it was possible to choose the best factors for preprocessing for a variety of situations through simulations. Further research related to this study needs to be carried out in the following topic : a study on the improvement of container performance by connecting the preprocessing with remarshalling.

On Narrowband Interference Suppression in OFDM-based Systems with CDMA and Weighted-type Fractional Fourier Transform Domain Preprocessing

  • Liang, Yuan;Da, Xinyu;Wang, Shu
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제11권11호
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    • pp.5377-5391
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    • 2017
  • In this paper, we propose a new scheme to suppress the narrowband interference (NBI) in OFDM-based systems. The scheme utilizes code division multiple access (CDMA) and weighted-type fractional Fourier transform (WFRFT) domain preprocessing technologies. Through setting the WFRFT order, the scheme can switch into a single carrier (SC) or a multi-carrier (MC) frequency division multiple access block transmission system. The residual NBI can be eliminated to the maximum extent when the WFRFT order is selected properly. Final simulation results show that the proposed system can outperform MC and SC with CDMA and frequency domain preprocessing in terms of the narrowband interference suppression.

얼굴 인식을 위한 Anisotropic smoothing 기반 조명 전처리 (Anisotropic based illumination Preprocessing for Face Recognition)

  • 김상훈;정선태;정수환;오두식;조성원
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 2007년도 하계종합학술대회 논문집
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    • pp.275-276
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    • 2007
  • In this paper, we propose an efficient illumination preprocessing algorithm for face recognition. One of the best known illumination preprocessing method, based on anisotropic smoothing, enhances the edge information, but instead deteriorates the contrast of the original image. Our proposed method reduces the deterioration of the contrast while enhancing the edge information, and thus the preprocessed image does not lose features like Gabor features of the original images much.. The effectiveness of the proposed illumination preprocessing method is verified through experiments of face recognition.

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효율적인 데이터베이스 마케팅을 위한 데이터마이닝 전처리도구에 관한 연구 (A Study on the Data Mining Preprocessing Tool For Efficient Database Marketing)

  • 이준석
    • 디지털융복합연구
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    • 제12권11호
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    • pp.257-264
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    • 2014
  • 효율적인 데이터베이스 마케팅을 위하여 고객들을 세분화하고, 새로운 지식을 탐색할 수 있는 데이터마이닝의 필요성이 증대되고 있다. 데이터마이닝 도구를 구축하기 위해서는 단계별 구현이 요구되어 지는데, 본 연구에서는 데이터마이닝을 위한 분산 환경에 적응 가능한 데이터 전처리 도구를 구성하였다. 기존의 데이터마이닝 도구인 앤서 트리, 클레멘타인, 엔터프라이즈 마이너, 캔싱턴, 웨카의 전처리 부분을 고찰하고, 분산 환경에서 효율적으로 사용할 수 있는 데이터 마이닝 전처리 도구를 구성하였다. 새로이 제안된 시스템은 엔터프라이즈 자바 빈즈와 XML을 기반으로 하였다.

전처리 방식의 복수지역 제약공정 스케줄링 (Preprocessing based Scheduling for Multi-Site Constraint Resources)

  • 홍민선;임석철;노승종
    • 한국경영과학회지
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    • 제33권1호
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    • pp.117-129
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    • 2008
  • Make-to-order manufacturers with multiple plants at multiple sites need to have the ability to quickly determine which plant will produce which customer order to meet the due date and minimize the transportation cost from the plants to the customer. Balancing the work loads and minimizing setups and make-span are also of great concern. Solving such scheduling problems usually takes a long time. We propose a new approach, which we call 'preprocessing', for resolving such complex problems. In preprocessing scheme, a 'good' a priori schedule is prepared and maintained using unconfirmed order information. Upon the confirmation of orders. the preprocessed schedule is quickly modified to obtain the final schedule. We present a preprocessing solution algorithm for multi-site constraint scheduling problem (MSCSP) using genetic algorithm; and conduct computational experiments to evaluate the performance of the algorithm.

Active Contour Model Based Object Contour Detection Using Genetic Algorithm with Wavelet Based Image Preprocessing

  • Mun, Kyeong-Jun;Kang, Hyeon-Tae;Lee, Hwa-Seok;Yoon, Yoo-Sool;Lee, Chang-Moon;Park, June-Ho
    • International Journal of Control, Automation, and Systems
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    • 제2권1호
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    • pp.100-106
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    • 2004
  • In this paper, we present a novel, rapid approach for the detection of brain tumors and deformity boundaries in medical images using a genetic algorithm with wavelet based preprocessing. The contour detection problem is formulated as an optimization process that seeks the contour of the object in a manner of minimizing an energy function based on an active contour model. The brain tumor segmentation contour, however, cannot be detected in case that a higher gradient intensity exists other than the interested brain tumor and deformities. Our method for discerning brain tumors and deformities from unwanted adjacent tissues is proposed. The proposed method can be used in medical image analysis because the exact contour of the brain tumor and deformities is followed by precise diagnosis of the deformities.

모바일 환경에서의 상황인식 기반 사용자 감성인지를 통한 개인화 서비스 (Personalized Service Based on Context Awareness through User Emotional Perception in Mobile Environment)

  • 권일경;이상용
    • 디지털융복합연구
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    • 제10권2호
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    • pp.287-292
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    • 2012
  • 본 논문에서는 모바일환경에서의 사용자 감정인지를 통한 개인화 서비스 지원에 필요한 위치기반 센싱 데이터의 전처리 기법과 사용자 감정 데이터의 구축 및 전처리를 위한 V-A 감정 모델에서의 감정 데이터 전처리 기법에 대하여 연구한다. 이를 위하여 그래뉼러 컨텍스트 트리 및 스트링 매칭 기반의 감정 패턴 매칭 기법을 사용한다. 또한 상황 인지를 통한 개인화 서비스를 위해 확률 기반 추론을 이용한 상황 인식 및 개인화 서비스 추천 기법에 대하여 연구한다.