• 제목/요약/키워드: Hybrid algorithms

검색결과 587건 처리시간 0.028초

Automatic Text Categorization Using Hybrid Multiple Model Schemes (하이브리드 다중모델 학습기법을 이용한 자동 문서 분류)

  • 명순희;김인철
    • Journal of the Korean Society for information Management
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    • 제19권4호
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    • pp.35-51
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    • 2002
  • Inductive learning and classification techniques have been employed in various research and applications that organize textual data to solve the problem of information access. In this study, we develop hybrid model combination methods which incorporate the concepts and techniques for multiple modeling algorithms to improve the accuracy of text classification, and conduct experiments to evaluate the performances of proposed schemes. Boosted stacking, one of the extended stacking schemes proposed in this study yields higher accuracy relative to the conventional model combination methods and single classifiers.

Genetic Algorithm based Hybrid Ensemble Model (유전자 알고리즘 기반 통합 앙상블 모형)

  • Min, Sung-Hwan
    • Journal of Information Technology Applications and Management
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    • 제23권1호
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    • pp.45-59
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    • 2016
  • An ensemble classifier is a method that combines output of multiple classifiers. It has been widely accepted that ensemble classifiers can improve the prediction accuracy. Recently, ensemble techniques have been successfully applied to the bankruptcy prediction. Bagging and random subspace are the most popular ensemble techniques. Bagging and random subspace have proved to be very effective in improving the generalization ability respectively. However, there are few studies which have focused on the integration of bagging and random subspace. In this study, we proposed a new hybrid ensemble model to integrate bagging and random subspace method using genetic algorithm for improving the performance of the model. The proposed model is applied to the bankruptcy prediction for Korean companies and compared with other models in this study. The experimental results showed that the proposed model performs better than the other models such as the single classifier, the original ensemble model and the simple hybrid model.

New buffer mapping method for Hybrid SPM with Buffer sharing (하이브리드 SPM을 위한 버퍼 공유를 활용한 새로운 버퍼 매핑 기법)

  • Lee, Daeyoung;Oh, Hyunok
    • IEMEK Journal of Embedded Systems and Applications
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    • 제11권4호
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    • pp.209-218
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    • 2016
  • This paper proposes a new lifetime aware buffer mapping method of a synchronous dataflow (SDF) graph on a hybrid memory system with DRAM and PRAM. Since the number of write operations on PRAM is limited, the number of written samples on PRAM is minimized to maximize the lifetime of PRAM. We improve the utilization of DRAM by mapping more buffers on DRAM through buffer sharing. The problem is formulated formally and solved by an optimal approach of an answer set programming. In experiment, the buffer mapping method with buffer sharing improves the PRAM lifetime by 63%.

NON-CONVEX HYBRID ALGORITHMS FOR A FAMILY OF COUNTABLE QUASI-LIPSCHITZ MAPPINGS CORRESPONDING TO KHAN ITERATIVE PROCESS AND APPLICATIONS

  • NAZEER, WAQAS;MUNIR, MOBEEN;NIZAMI, ABDUL RAUF;KAUSAR, SAMINA;KANG, SHIN MIN
    • Journal of applied mathematics & informatics
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    • 제35권3_4호
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    • pp.313-321
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    • 2017
  • In this note we establish a new non-convex hybrid iteration algorithm corresponding to Khan iterative process [4] and prove strong convergence theorems of common fixed points for a uniformly closed asymptotically family of countable quasi-Lipschitz mappings in Hilbert spaces. Moreover, the main results are applied to get the common fixed points of finite family of quasi-asymptotically nonexpansive mappings. The results presented in this article are interesting extensions of some current results.

The Development of a Model for Vehicle Type Classification with a Hybrid GLVQ Neural Network (복합형GLVQ 신경망을 이용한 차종분류 모형개발)

  • 조형기;오영태
    • Journal of Korean Society of Transportation
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    • 제14권4호
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    • pp.49-76
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    • 1996
  • Until recently, the inductive loop detecters(ILD) have been used to collect a traffic information in a part of traffic manangment and control. The ILD is able to collect a various traffic data such as a occupancy time and non-occupancy time, traffic volume, etc. The occupancy time of these is very important information for traffic control algorithms, which is required a high accuracy. This accuracy may be improved by classifying a vehicle type with ILD. To classify a vehicle type based on a Analog Digital Converted data collect form ILD, this study used a typical and modifyed statistic method and General Learning Vector Quantization unsuperviser neural network model and a hybrid model of GLVQ and statistic method, As a result, the hybrid model of GLVQ neural network model is superior to the other methods.

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A Nodes Set Based Hybrid Evolutionary Strategy on the Rectilinear Steiner Tree Problem (점집합을 개체로 이용한 직각거리 스타이너 나무 문제의 하이브리드 진화 전략에 관한 연구)

  • Yang Byoung-Hak
    • Korean Management Science Review
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    • 제23권1호
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    • pp.75-85
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    • 2006
  • The rectilinear Steiner tree problem (RSTP) is to find a minimum-length rectilinear interconnection of a set of terminals in the plane. It is well known that the solution to this problem will be the minimal spanning tree(MST) on some set Steiner points. The RSTP is known to be NP-complete. The RSTP has received a lot of attention in the literature and heuristic and optimal algorithms have been proposed. A key performance measure of the algorithm for the RSTP is the reduction rate that is achieved by the difference between the objective value of the RSTP and that of the MST without Steiner points. A hybrid evolutionary strategy on RSTP based upon nodes set is presented. The computational results show that the hybrid evolutionary strategy is better than the previously proposed other heuristic. The average reduction rate of solutions from the evolutionary strategy is about 11.14%, which is almost similar to that of optimal solutions.

A Hybrid Decimal Division Algorithm

  • Kwon Soonyoul;Choi Jonghwa;Park Jinsub;Han Seonkyoung;You Younggap
    • Proceedings of the IEEK Conference
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    • 대한전자공학회 2004년도 ICEIC The International Conference on Electronics Informations and Communications
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    • pp.225-228
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    • 2004
  • This paper presents a hybrid decimal division algorithm to improve division speed. In a binary number system, non-restoring algorithm has a smaller number of operations than restoring algorithm. In decimal number system, however, the number of operations differs with respect to quotient values. Since one digit ranges 0 to 9 in decimal, the proposed hybrid algorithm employ either non-restoring or restoring algorithm on each digit to reduce iterative operations. The selection of the algorithm is based on the remainder values. The proposed algorithm improves computation speed substantially over conventional algorithms by decreasing the number of operations.

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A hybrid approach for character modeling using geometric primitives and shape-from-shading algorithm

  • Kazmin, Ismail Khalid;You, Lihua;Zhang, Jian Jun
    • Journal of Computational Design and Engineering
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    • 제3권2호
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    • pp.121-131
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    • 2016
  • Organic modeling of 3D characters is a challenging task when it comes to correctly modeling the anatomy of the human body. Most sketch based modeling tools available today for modeling organic models (humans, animals, creatures etc) are focused towards modeling base mesh models only and provide little or no support to add details to the base mesh. We propose a hybrid approach which combines geometrical primitives such as generalized cylinders and cube with Shape-from-Shading (SFS) algorithms to create plausible human character models from sketches. The results show that an artist can quickly create detailed character models from sketches by using this hybrid approach.

Binary image compression with morphological hybrid structuring elements (이진 형태론의 Hybrid 형태소에 의한 압축)

  • 정기룡;김신환;김두영;김명기
    • The Journal of Korean Institute of Communications and Information Sciences
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    • 제21권9호
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    • pp.2317-2327
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    • 1996
  • Original binary image can be reconstructed without any distortion by MS(morphological skeleton) image. Though we reduce some points in a MS image, there is no problem to reconstruct original image by it. And then, there are two methods of LMS and GMS which reduce the redundant points of a MS image. The redundancy degree of a GMS image is zero and it is less than that of LMS. And then, GMS image is the best thing of the three kinds of morphological skeleton image to enhance the compression efficienty by the Elias code. But there are continous SKF=1 points in a GMS image whenever using 2 dimensional structureing element. Those points in a GMS image gives rise to a bad compression efficiency. And then, solving this problem, this paper proposes hybrid structuring elements algorithms for binary image compression.

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GENIIS, a New Hybrid Algorithm for Solving the Mixed Chinese Postman Problem

  • Choi, Myeong-Gil;Thangi, Nguyen-Manh;Hwang, Won-Joo
    • The Journal of Information Systems
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    • 제17권3호
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    • pp.39-58
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    • 2008
  • Mixed Chinese Postman Problem (MCPP) is a practical generalization of the classical Chinese Postman Problem (CPP) and it could be applied in many real world. Although MCPP is useful in terms of reality, MCPP has been proved to be a NP-complete problem. To find optimal solutions efficiently in MCPP, we can reduce searching space to be small effective searching space containing optimal solutions. We propose GENIIS methodology, which is a kind of hybrid algorithm combines the approximate algorithms and genetic algorithm. To get good solutions in the effective searching space, GENIIS uses approximate algorithm and genetic algorithm. This paper validates the usefulness of the proposed approach in a simulation. The results of our paper could be utilized to increase the efficiencies of network and transportation in business.