• Title/Summary/Keyword: Changing algorithm

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Optimization of parameters in mobile robot navigation using genetic algorithm (유전자 알고리즘을 이용한 이동 로봇 주행 파라미터의 최적화)

  • 김경훈;조형석
    • 제어로봇시스템학회:학술대회논문집
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    • 1996.10b
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    • pp.1161-1164
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    • 1996
  • In this paper, a parameter optimization technique for a mobile robot navigation is discussed. Authors already have proposed a navigation algorithm for mobile robots with sonar sensors using fuzzy decision making theory. Fuzzy decision making selects the optimal via-point utilizing membership values of each via-point candidate for fuzzy navigation goals. However, to make a robot successfully navigate through an unknown and cluttered environment, one needs to adjust parameters of membership function, thus changing shape of MF, for each fuzzy goal. Furthermore, the change in robot configuration, like change in sensor arrangement or sensing range, invokes another adjusting of MFs. To accomplish an intelligent way to adjust these parameters, we adopted a genetic algorithm, which does not require any formulation of the problem, thus more appropriate for robot navigation. Genetic algorithm generates the fittest parameter set through crossover and mutation operation of its string representation. The fitness of a parameter set is assigned after a simulation run according to its time of travel, accumulated heading angle change and collision. A series of simulations for several different environments is carried out to verify the proposed method. The results show the optimal parameters can be acquired with this method.

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Adaptive Nulling Algorithm for Null Synthesis on the Moving Jammer Environment (이동형 재밍환경에서 널 합성을 위한 적응형 널링 알고리즘)

  • Seo, Jongwoo;Park, Dongchul
    • The Journal of Korean Institute of Electromagnetic Engineering and Science
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    • v.27 no.8
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    • pp.676-683
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    • 2016
  • In this paper, an adaptive nulling algorithm which can be used to form nulls in the direction of jammer or interference signals in array antennas of single port system is proposed. The proposed adaptive algorithm does not require a priori knowledge of the incoming signal direction and can be applied to the partially adaptive arrays. This algorithm is the combination of the PSO(Particle Swam Optimization) algorithm and the gradient-based perturbation adaptive algorithm, which shows stable nulling performance adaptively even on the moving jammer environment where the incident direction of the interference signal is changing with time.

Defect Cell Extraction for TFT-LCD Auto-Repair System (TFT-LCD 자동 수선시스템에서 결함이 있는 셀을 자동으로 추출하는 방법)

  • Cho, Jae-Soo;Ha, Gwang-Sung;Lee, Jin-Wook;Kim, Dong-Hyun;Jeon, Edward
    • Journal of Institute of Control, Robotics and Systems
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    • v.14 no.5
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    • pp.432-437
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    • 2008
  • This paper proposes a defect cell extraction algorithm for TFT-LCD auto-repair system. Auto defect search algorithm and automatic defect cell extraction method are very important for TFT-LCD auto repair system. In the previous literature[1], we proposed an automatic visual inspection algorithm of TFT-LCD. Based on the inspected information(defect size and defect axis, if defect exists) by the automatic search algorithm, defect cells should be extracted from the input image for the auto repair system. For automatic extraction of defect cells, we used a novel block matching algorithm and a simple filtering process in order to find a given reference point in the LCD cell. The proposed defect cell extraction algorithm can be used in all kinds of TFT-LCD devices by changing a stored template which includes a given reference point. Various experimental results show the effectiveness of the proposed method.

Genetic Algorithm based hyperparameter tuned CNN for identifying IoT intrusions

  • Alexander. R;Pradeep Mohan Kumar. K
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.18 no.3
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    • pp.755-778
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    • 2024
  • In recent years, the number of devices being connected to the internet has grown enormously, as has the intrusive behavior in the network. Thus, it is important for intrusion detection systems to report all intrusive behavior. Using deep learning and machine learning algorithms, intrusion detection systems are able to perform well in identifying attacks. However, the concern with these deep learning algorithms is their inability to identify a suitable network based on traffic volume, which requires manual changing of hyperparameters, which consumes a lot of time and effort. So, to address this, this paper offers a solution using the extended compact genetic algorithm for the automatic tuning of the hyperparameters. The novelty in this work comes in the form of modeling the problem of identifying attacks as a multi-objective optimization problem and the usage of linkage learning for solving the optimization problem. The solution is obtained using the feature map-based Convolutional Neural Network that gets encoded into genes, and using the extended compact genetic algorithm the model is optimized for the detection accuracy and latency. The CIC-IDS-2017 and 2018 datasets are used to verify the hypothesis, and the most recent analysis yielded a substantial F1 score of 99.23%. Response time, CPU, and memory consumption evaluations are done to demonstrate the suitability of this model in a fog environment.

A study on the hydrodynamic coefficients estimation of an underwater vehicle (수중운동체의 유체계수 추정에 관한 연구)

  • Yang, Seung-Yun;Lee, Man-Hyung
    • Journal of Institute of Control, Robotics and Systems
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    • v.2 no.2
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    • pp.121-126
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    • 1996
  • The hydrodynamic coefficients estimation (HCE) is important to design the autopilot and to predict the maneuverability of an underwater vehicle. In this paper, a system identification is proposed for an HCE of an underwater vehicle. First, we attempt to design the HCE algorithm which is insensitive to initial conditions and has good convergence, and which enables the estimation of the coefficents by using measured displacements only. Second, the sensor and measurement system which gauges the data from the full scale trials is constructed and the data smoothing algorithm is also designed to filter the noise due to irregular fluid flow without changing the data characteristics itself. Lastly the hydrodynamic coefficients are estimated by applying the measured data of full scale trials to the developed algorithm, and the estimated coefficients are verified by full scale trials.

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Development of a Transportation Planning System for the Mail Transportation Network (우편운송망에서의 운송편 관리를 위한 교환/집중국망 상시조정시스템 개발)

  • Choi, Ji-Young;Kim, Wan-Seok;Park, Jong-Heung;Lee, Tae-Han
    • IE interfaces
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    • v.21 no.1
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    • pp.120-130
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    • 2008
  • In this paper, we develop a transportation planning system for the mail transportation network, which consists of 25 mail centers and one mail exchange center. The main functions of the system are adjustment of transportation plan, creation of new transportation plan, and calculation of expected exchange mail volume which are transported through mail exchange center. We develop an adjusting algorithm which gives a new transportation plan by deleting, adding or changing the current routes. The algorithm based on the transportation results of current transportation plan and mail volume data. We design and implement a planning system by installing the algorithm as the planning engine. For the practical use, the system is connected to the information system of Korea Post, PostNet.

A Study on Fuzzy Controller for Autonomous Mobile Robot (자율 이동 로보트의 퍼지 제어기에 관한 연구)

  • 주영훈;황희수;고재원;김성권;황금찬;우광방
    • The Transactions of the Korean Institute of Electrical Engineers
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    • v.41 no.9
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    • pp.1071-1084
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    • 1992
  • In this paper, the method for navigation and obstacle avoidance of the autonomous mobile robot is proposed. The proposed algorithms are based on the fuzzy inference system which is able to deal with imprecise and uncertain information. The self-tuning algorithm, which adopts the simplex method, modifies the parameters of membership functions of the input-output linguistic variables by changing the support of these fuzzy sets according to the integral of absolute error(IAE) of the system response. The wall-follwing navigation and obstacle avoidance of the mobile robot are based on range data measured from the internal sensors(encoder) and the outer sensors(sonar sensor). In addition, the algorithm for the obstacle detection proposed in this paper is based on the expert's experience. Finally, the effectiveness of navigation and obstacle avoidance algorithm is demonstrated through simulation and experiment.

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Study on Incident Detection System Using Fuzzy Logic

  • Kim, Intaek;Lee, Eunggi
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 1998.06a
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    • pp.268-271
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    • 1998
  • this paper presents the potential application of fuzzy logic to the automatic incident detection system. While the conventional incident detection algorithms are based on a binary decision process, the algorithm using fuzzy logic can incorporate ambiguity which occurs in determining incidents. Since collecting good amount of data to construct data base for incidents is pretty expensive, a traffic simulator called FRESIM is used to simulate traffic condition in a freeway. Incident data are obtained by changing input parameters of the simulator and the fuzzy algorithm generates fuzzy rule for determining normal and incident traffic conditions. In this paper, various steps are described to test the algorithm and its results are summarized.

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Regrouping Service Sites: a Genetic Approach using a Voronoi Diagram (서비스 위치 그룹핑을 위한 보로노이 다이어그램 기반의 유전자알고리듬)

  • Seo, Jeong-Yeon;Park, Sang-Min;Jeong, In-Jae;Kim, Deok-Soo
    • Proceedings of the Korean Operations and Management Science Society Conference
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    • 2005.05a
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    • pp.179-187
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    • 2005
  • In this paper, we consider the problem of regrouping a number of service sites into a smaller number of service sites called centers. Each service site is represented as a point in the plane and has an associated value of service demand. We aim to group the sites so that each group has the balanced service demand and the sum of distances from the sites in the group to their corresponding center is minimized. To solve this problem, we propose a hybrid genetic algorithm that is combined with Voronoi diagrams. We provide a variety of experimental results by changing the weights of the two factors: service demands and distances. Our hybrid algorithm finds better solutions in a shorter computation time in comparison with a pure genetic algorithm.

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Complexity Reduction Algorithm of Speech Coder(EVRC) for CDMA Digital Cellular System

  • Min, So-Yeon
    • Journal of Korea Multimedia Society
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    • v.10 no.12
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    • pp.1551-1558
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    • 2007
  • The standard of evaluating function of speech coder for mobile telecommunication can be shown in channel capacity, noise immunity, encryption, complexity and encoding delay largely. This study is an algorithm to reduce complexity applying to CDMA(Code Division Multiple Access) mobile telecommunication system, which has a benefit of keeping the existing advantage of telecommunication quality and low transmission rate. This paper has an objective to reduce the computing complexity by controlling the frequency band nonuniform during the changing process of LSP(Line Spectrum Pairs) parameters from LPC(Line Predictive Coding) coefficients used for EVRC(Enhanced Variable-Rate Coder, IS-127) speech coders. Its experimental result showed that when comparing the speech coder applied by the proposed algorithm with the existing EVRC speech coder, it's decreased by 45% at average. Also, the values of LSP parameters, Synthetic speech signal and Spectrogram test result were obtained same as the existing method.

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