• 제목/요약/키워드: Method selection

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효율적 망 자원 이용을 위한 부하 인지 셀 선택 기법 (Load-Aware Cell Selection Method for Efficient Use of Network Resources)

  • 박재성
    • 한국통신학회논문지
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    • 제40권12호
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    • pp.2443-2449
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    • 2015
  • 단말이 망에서 제공받는 데이터 전송율은 단말과 셀 사이의 SINR 뿐만 아니라 셀이 단말에게 할당하는 무선 자원양에 의해서도 결정된다. 따라서 단말이 SINR만을 기준으로 접속할 셀을 선택하면 비록 최대 SINR을 제공하는 셀에 접속한다고 하더라도 최대 서비스율을 제공받지 못할 수도 있다. 또한 네트워크의 입장에서는 SINR을 기준으로 접속 셀이 선택되므로 일부 셀들은 다수의 단말이 접속하는 반면 주변의 다른 셀들은 접속 단말의 수가 적게 되어 셀간 부하 불균형 상태가 발생될 확률이 커지고 이로 인해 이동 통신 시스템의 자원 이용율이 낮아지게 된다. 이에따라 본 논문에서는 SINR뿐만 아니라 셀의 부하를 고려한 접속 셀 선택 방법을 제안한다. 이를 위해 접속 셀 선택 지표로 SINR 대신에 최대 데이터 전송율과 최소 전송율 단절 확률을 제시한다. 제안 기법의 성능 평가를 위한 모의실험 결과 최대 데이터 전송율을 이용한 셀 선택 방법은 타 기법에 비해 시스템 효율과 셀간 부하 균등 측면에서 향상된 성능을 보였으며 최소 전송율 단절 확률을 이용한 셀 선택 방법은 타 기법에 비해 단말의 평균 전송율 단절 확률 측면에서 향상된 성능을 보였다.

상호정보량과 Binary Particle Swarm Optimization을 이용한 속성선택 기법 (Feature Selection Method by Information Theory and Particle S warm Optimization)

  • 조재훈;이대종;송창규;전명근
    • 한국지능시스템학회논문지
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    • 제19권2호
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    • pp.191-196
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    • 2009
  • 본 논문에서는 BPSO(Binary Particle Swarm Optimization)방법과 상호정보량을 이용한 속성선택기법을 제안한다. 제안된 방법은 상호정보량을 이용한 후보속성부분집합을 선택하는 단계와 BPSO를 이용한 최적의 속성부분집합을 선택하는 단계로 구성되어 있다. 후보속성부분집합 선택 단계에서는 독립적으로 속성들의 상호정보량을 평가하여 순위별로 설정된 수 만큼 후보속성들을 선택한다. 최적속성부분집합 선택 단계에서는 BPSO를 이용하여 후보속성부분집합에서 최적의 속성부분집합을 탐색한다. BPSO의 목적함수는 분류기의 정확도와 선택된 속성 수를 포함하는 다중목적함수(Multi-Object Function)을 이용하였다. 제안된 기법의 성능을 평가하기 위하여 유전자 데이터를 사용하였으며, 실험결과 기존의 방법들에 비해 우수한 성능을 보임을 알 수 있었다.

동적 프로그래밍에 기반한 윤곽선 근사화를 위한 정점 선택 방법 (Vertex Selection Scheme for Shape Approximation Based on Dynamic Programming)

  • 이시웅;최재각;남재열
    • 대한전자공학회논문지SP
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    • 제41권3호
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    • pp.121-127
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    • 2004
  • This paper presents a new vertex selection scheme for shape approximation. In the proposed method, final vertex points are determined by "two-step procedure". In the first step, initial vertices are simply selected on the contour, which constitute a subset of the original contour, using conventional methods such as an iterated refinement method (IRM) or a progressive vertex selection (PVS) method In the second step, a vertex adjustment Process is incorporated to generate final vertices which are no more confined to the contour and optimal in the view of the given distortion measure. For the optimality of the final vertices, the dynamic programming (DP)-based solution for the adjustment of vertices is proposed. There are two main contributions of this work First, we show that DP can be successfully applied to vertex adjustment. Second, by using DP, the global optimality in the vertex selection can be achieved without iterative processes. Experimental results are presented to show the superiority of our method over the traditional methods.

특징 선택과 융합 방법을 이용한 음성 감정 인식 (Speech Emotion Recognition using Feature Selection and Fusion Method)

  • 김원구
    • 전기학회논문지
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    • 제66권8호
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    • pp.1265-1271
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    • 2017
  • In this paper, the speech parameter fusion method is studied to improve the performance of the conventional emotion recognition system. For this purpose, the combination of the parameters that show the best performance by combining the cepstrum parameters and the various pitch parameters used in the conventional emotion recognition system are selected. Various pitch parameters were generated using numerical and statistical methods using pitch of speech. Performance evaluation was performed on the emotion recognition system using Gaussian mixture model(GMM) to select the pitch parameters that showed the best performance in combination with cepstrum parameters. As a parameter selection method, sequential feature selection method was used. In the experiment to distinguish the four emotions of normal, joy, sadness and angry, fifteen of the total 56 pitch parameters were selected and showed the best recognition performance when fused with cepstrum and delta cepstrum coefficients. This is a 48.9% reduction in the error of emotion recognition system using only pitch parameters.

Lung Cancer Risk Prediction Method Based on Feature Selection and Artificial Neural Network

  • Xie, Nan-Nan;Hu, Liang;Li, Tai-Hui
    • Asian Pacific Journal of Cancer Prevention
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    • 제15권23호
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    • pp.10539-10542
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    • 2015
  • A method to predict the risk of lung cancer is proposed, based on two feature selection algorithms: Fisher and ReliefF, and BP Neural Networks. An appropriate quantity of risk factors was chosen for lung cancer risk prediction. The process featured two steps, firstly choosing the risk factors by combining two feature selection algorithms, then providing the predictive value by neural network. Based on the method framework, an algorithm LCRP (lung cancer risk prediction) is presented, to reduce the amount of risk factors collected in practical applications. The proposed method is suitable for health monitoring and self-testing. Experiments showed it can actually provide satisfactory accuracy under low dimensions of risk factors.

주성분 분석 로딩 벡터 기반 비지도 변수 선택 기법 (Unsupervised Feature Selection Method Based on Principal Component Loading Vectors)

  • 박영준;김성범
    • 대한산업공학회지
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    • 제40권3호
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    • pp.275-282
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    • 2014
  • One of the most widely used methods for dimensionality reduction is principal component analysis (PCA). However, the reduced dimensions from PCA do not provide a clear interpretation with respect to the original features because they are linear combinations of a large number of original features. This interpretation problem can be overcome by feature selection approaches that identifying the best subset of given features. In this study, we propose an unsupervised feature selection method based on the geometrical information of PCA loading vectors. Experimental results from a simulation study demonstrated the efficiency and usefulness of the proposed method.

Evaluation of GIS-supported Route Selection Method of Hillside Transportation in Nagasaki City, Japan

  • Watanabe, Kohei;Gotoh, Keinosuke;Tachiiri, Kaoru
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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    • pp.543-545
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    • 2003
  • In this study, the authors evaluate the suitability of the candidate routes selected by the route selection method, which is developed by the authors, by combination of Geographic Information Systems (GIS) and Analytic Hierarchy Process. To evaluate the suitability of the candidate routes, from the viewpoint of the residents, we have considered element factors such as, population, household, aging situation, elevation, gradient, housing density and the Control Point. The results of this study are expected to assess the suitability of the candidate routes of the hillside transportation for the residents and examine the application limit of the route selection method.

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Hybrid Feature Selection Method Based on a Naïve Bayes Algorithm that Enhances the Learning Speed while Maintaining a Similar Error Rate in Cyber ISR

  • Shin, GyeongIl;Yooun, Hosang;Shin, DongIl;Shin, DongKyoo
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제12권12호
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    • pp.5685-5700
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    • 2018
  • Cyber intelligence, surveillance, and reconnaissance (ISR) has become more important than traditional military ISR. An agent used in cyber ISR resides in an enemy's networks and continually collects valuable information. Thus, this agent should be able to determine what is, and is not, useful in a short amount of time. Moreover, the agent should maintain a classification rate that is high enough to select useful data from the enemy's network. Traditional feature selection algorithms cannot comply with these requirements. Consequently, in this paper, we propose an effective hybrid feature selection method derived from the filter and wrapper methods. We illustrate the design of the proposed model and the experimental results of the performance comparison between the proposed model and the existing model.

포켓형상가공을 위한 최적공구 선정방법 (An Optimal Tool Selection Method for Pocket Machining)

  • 경영민;조규갑;전차수
    • 한국정밀공학회지
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    • 제14권7호
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    • pp.49-58
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    • 1997
  • In process planning for pocket machining, the selection of tool size, tool path, overlap distance, and the calculation of machining time are very important factors to obtain the optimal process planning result. Among those factors, the tool size is the most important one because the others depend on tool size. And also, it is not easy to determine the optimal tool size even though the shape of pocket is simple. Therefore, the optimal selection of tool size is the most essential task in process planning for machining a pocket. This paper presents a method for selecting optimal toos in pocket machining. The branch and bound method is applied to select the optimal tools which minimize the machining time by using the range of feasible tools and the breadth-first search.

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Multi-Dimensional Selection Method of Port Logistics Location Based on Entropy Weight Method

  • Ruiwei Guo
    • Journal of Information Processing Systems
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    • 제19권4호
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    • pp.407-416
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    • 2023
  • In order to effectively relieve the traffic pressure of the city, ensure the smooth flow of freight and promote the development of the logistics industry, the selection of appropriate port logistics location is the basis of giving full play to the port logistics function. In order to better realize the selection of port logistics, this paper adopts the entropy weight method to set up a multi-dimensional evaluation index, and constructs the evaluation model of port logistics location. Then through the actual case, from the environmental dimension and economic competition dimension to make choices and analysis. The results show that port d has the largest logistics competitiveness and the highest relative proximity among the three indicators of hinterland city economic activity, hinterland economic structure, and port operation capacity of different port logistics locations, which has absolute advantages. It is hoped that the research results can provide a reference for the multi-dimensional selection of port logistics site selections.