• 제목/요약/키워드: Intelligent Algorithm

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Table based Single Pass Algorithm for Clustering News Articles

  • Jo, Tae-Ho
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • 제8권3호
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    • pp.231-237
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    • 2008
  • This research proposes a modified version of single pass algorithm specialized for text clustering. Encoding documents into numerical vectors for using the traditional version of single pass algorithm causes the two main problems: huge dimensionality and sparse distribution. Therefore, in order to address the two problems, this research modifies the single pass algorithm into its version where documents are encoded into not numerical vectors but other forms. In the proposed version, documents are mapped into tables and the operation on two tables is defined for using the single pass algorithm. The goal of this research is to improve the performance of single pass algorithm for text clustering by modifying it into the specialized version.

A Novel Optimization Algorithm Inspired by Bacteria Behavior Patterns

  • 정성훈;김태건
    • 한국지능시스템학회논문지
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    • 제18권3호
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    • pp.392-400
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    • 2008
  • This paper proposes a novel optimization algorithm inspired by bacteria behavior patterns for foraging. Most bacteria can trace attractant chemical molecules for foraging. This tracing capability of bacteria called chemotaxis might be optimized for foraging because it has been evolved for few millenniums. From this observation, we developed a new optimization algorithm based on the chemotaxis of bacteria in this paper. We first define behavior and decision rules based on the behavior patterns of bacteria and then devise an optimization algorithm with these behavior and decision rules. Generally bacteria have a quorum sensing mechanism that makes it possible to effectively forage, but we leave its implementation as a further work for simplicity. Thereby, we call our algorithm a simple bacteria cooperative optimization (BCO) algorithm. Our simple BCO is tested with four function optimization problems on various' parameters of the algorithm. It was found from experiments that the simple BCO can be a good framework for optimization.

STAR-24K: A Public Dataset for Space Common Target Detection

  • Zhang, Chaoyan;Guo, Baolong;Liao, Nannan;Zhong, Qiuyun;Liu, Hengyan;Li, Cheng;Gong, Jianglei
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제16권2호
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    • pp.365-380
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    • 2022
  • The target detection algorithm based on supervised learning is the current mainstream algorithm for target detection. A high-quality dataset is the prerequisite for the target detection algorithm to obtain good detection performance. The larger the number and quality of the dataset, the stronger the generalization ability of the model, that is, the dataset determines the upper limit of the model learning. The convolutional neural network optimizes the network parameters in a strong supervision method. The error is calculated by comparing the predicted frame with the manually labeled real frame, and then the error is passed into the network for continuous optimization. Strongly supervised learning mainly relies on a large number of images as models for continuous learning, so the number and quality of images directly affect the results of learning. This paper proposes a dataset STAR-24K (meaning a dataset for Space TArget Recognition with more than 24,000 images) for detecting common targets in space. Since there is currently no publicly available dataset for space target detection, we extracted some pictures from a series of channels such as pictures and videos released by the official websites of NASA (National Aeronautics and Space Administration) and ESA (The European Space Agency) and expanded them to 24,451 pictures. We evaluate popular object detection algorithms to build a benchmark. Our STAR-24K dataset is publicly available at https://github.com/Zzz-zcy/STAR-24K.

Experimental Studies of Force Control for Crack Sealing Robot

  • Jeon, Poong-Woo;Cho, Hyun-Taek;Jung, Seul
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2003년도 ICCAS
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    • pp.1077-1081
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    • 2003
  • In this paper, experimental studies of force tracking control for the crack sealing robot are presented. Crack sealing robot is built to detect, track and seal the crack on the pavement. Before sealing, crack must be detected by a laser sensor and a camera sensor, then cleaned for a better sealing job. In order to maintain contact with the ground force control is required to brush all dirt in the crack out for preparing sealing cracks with tars. Impedance control algorithm is presented to regulate a specified desired force. Experimental studies of the proposed force control algorithm are conducted under unknown environment stiffness and location. Performances of force control algorithm are stable and excellent.

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Development of the automatic tunneling algorithm based on fuzzy logic for the microtunneling system

  • Han, Jeong-Su;Do, Jun-Hyeong;Zeungnam Bien;Janghyun Nam;Park, Taedong;Park, Kwang-Hyun
    • 한국지능시스템학회:학술대회논문집
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    • 한국퍼지및지능시스템학회 2003년도 ISIS 2003
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    • pp.676-678
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    • 2003
  • Microtunneling techniques play a crucial role in the construction of pipelines. This paper shows the automatic tunneling algorithm of microtunneling system using fuzzy logic technology to assist operators to assure the quality of microtunneling construction. To have effective output value of fuzzy controller, we slightly modified the conventional defuzzification methods. The proposed automatic tunneling algorithm shows good tunneling results comparable with those of experts.

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실시간 산업환경을 위한 IEEE 802.11기반 가상 폴링 알고리즘 개발 (Development of IEEE 802.11 based virtual polling algorithm for real time industrial environments)

  • 박지훈;하경남;이경창;이석
    • 한국정밀공학회:학술대회논문집
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    • 한국정밀공학회 2005년도 춘계학술대회 논문집
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    • pp.1013-1017
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    • 2005
  • This paper proposes an effective algorithm, P-DCF(Polling DCF) to satisfy real-time requirements in the industrial environments, based on 802.11 DCF protocols. Theoretical analysis and actual experiments are carried out, which shows that the proposed P-DCF brings several benefits: 1) it reduces the time delay for frame transmission 2)it guarantees bounded upper limit of maximum transmission delay 3) it maintains fairness

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하이브리드 데이터마이닝을 이용한 지능형 이상 진단 시스템 (Intelligent Fault Diagnosis System Using Hybrid Data Mining)

  • 백준걸;허준
    • 한국경영과학회:학술대회논문집
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    • 한국경영과학회/대한산업공학회 2005년도 춘계공동학술대회 발표논문
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    • pp.960-968
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    • 2005
  • The high cost in maintaining complex manufacturing process makes it necessary to enhance an efficient maintenance system. For the effective maintenance of manufacturing process, precise fault diagnosis should be performed and an appropriate maintenance action should be executed. This paper suggests an intelligent fault diagnosis system using hybrid data mining. In this system, the rules for the fault diagnosis are generated by hybrid decision tree/genetic algorithm and the most effective maintenance action is selected by decision network and AHP. To verify the proposed intelligent fault diagnosis system, we compared the accuracy of the hybrid decision tree/genetic algorithm with one of the general decision tree learning algorithm(C4.5) by data collected from a coil-spring manufacturing process.

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The Hybrid Knowledge Integration Using the Fuzzy Genetic Algorithm

  • Kim, Myoung-Jong;Ingoo Han;Lee, Kun-Chang
    • 한국지능정보시스템학회:학술대회논문집
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    • 한국지능정보시스템학회 1999년도 춘계공동학술대회-지식경영과 지식공학
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    • pp.145-154
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    • 1999
  • An intelligent system embedded with multiple sources of knowledge may provide more robust intelligence with highly ill structured problems than the system with a single source of knowledge. This paper proposes th hybrid knowledge integration mechanism that yields the cooperated knowledge by integrating expert, user, and machine knowledge within the fuzzy logic-driven framework, and then refines it with a genetic algorithm (GA) to enhance the reasoning performance. The proposed knowledge integration mechanism is applied for the prediction of Korea stock price index (KOSPI). Empirical results show that the proposed mechanism can make an intelligent system with the more adaptable and robust intelligence.

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theory and implementation

  • Lee, Young-Q.;Kumara, Soundar R.T.;Ham, Inyong
    • 한국경영과학회:학술대회논문집
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    • 대한산업공학회/한국경영과학회 1992년도 춘계공동학술대회 발표논문 및 초록집; 울산대학교, 울산; 01월 02일 May 1992
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    • pp.533-544
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    • 1992
  • 한 제품의 구성 부품 수가 증가함에 따라 조립/분해 순서의 방법수는 기하급수적으로 증가한다. 또한 이 순서의 선택에 의하여 조립/분해의 효율성이 결정된다. 본 논문에서는 조립제품의 조립순서(Assembly Sequence)와 특정부품의 효율적 교체(Part Replacement)를 위한 분해순서(Disassembly sequence)에 관한 새로운 Algorithm들을 다음 3가지 경우를 통하여 소개한다 : 1) Full Assembly/Disassembly, 2) Part Replacement by Individual Disassembly, 그리고 3) Part Replacement by Group Disassembly. 이들 Algorithm들은 'Freedom and Interference Space'라는 새로운 개념으로부터 유도되며, Group Disassembly는 Carpenter's Approach를 통하여 실현된다. 이 논문에서 소개되는 Algorithm들은 조립/분해순서와 함께 조립/분해 방향도 제시하는데 비교적 복잡한 예를 통하여 이들을 실현함으로써 실제 제품 Design에의 활용 가능성을 보여준다.

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Design of Target Tracking System Using a New Intelligent Algorithm

  • Noh, Sun-Young;Joo, Young-Hoon;Park, Jin-Bae
    • 한국지능시스템학회논문지
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    • 제15권6호
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    • pp.748-753
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    • 2005
  • When the maneuver occurs, the performance of the standard Kalman filter has been degraded because mismatches between the modeled target dynamics and the actual target dynamics. To solve this problem, the unknown acceleration is determined by using the fuzzy logic based on genetic algorithm(GA) method. This algorithm is the method to estimate the increment of acceleration by a fuzzy system using th relation between maneuver filler residual and non-maneuvering one. To optimize this system, a GA is utilized. And then, the modified filter is corrected by the new update equation method which is a fuzzy system using the relation between the filter residual and its variation. To shows the feasibility of the suggested method with only one filter, the computer simulations system are provided, this method is compared with multiple model method.