• Title/Summary/Keyword: Proposed model

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GA-Based IMM Method for Tracking a Maneuvering Target (기동 표적 추적을 위한 유전 알고리즘 기반 상호 작용 다중 모델 기법)

  • Lee, Bum-Jik;Joo, Young-Hoon;Park, Jin-Bae
    • Proceedings of the KIEE Conference
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    • 2002.07d
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    • pp.2382-2384
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    • 2002
  • The accuracy in maneuvering target tracking using multiple models is caused by the suitability of each target motion model to be used. The interacting multiple model (IMM) algorithm and the adaptive IMM (AIMM) algorithm require the predefined sub-models and the predetermined acceleration intervals, respectively, in consideration of the properties of maneuvers in order to construct multiple models. In this paper, to solve these problems intelligently, a genetic algorithm (GA) based-IMM method using fuzzy logic is proposed. In the proposed method, the acceleration input is regarded as an additive noise and a sub-model is represented as a set of fuzzy rules to model the time-varying variances of the process noises of a new piecewise constant white acceleration model. The proposed method is compared with the AIMM algorithm in simulations.

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Development of the Drop-outs Prediction Model for Intelligent Drop-outs Prevention System

  • Song, Mi-Young
    • Journal of the Korea Society of Computer and Information
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    • v.22 no.10
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    • pp.9-17
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    • 2017
  • The student dropout prediction is an indispensable for many intelligent systems to measure the educational system and success rate of all university. Therefore, in this paper, we propose an intelligent dropout prediction system that minimizes the situation by adopting the proactive process through an effective model that predicts the students who are at risk of dropout. In this paper, the main data sets for students dropout predictions was used as questionnaires and university information. The questionnaire was constructed based on theoretical and empirical grounds about factor affecting student's performance and causes of dropout. University Information included student grade, interviews, attendance in university life. Through these data sets, the proposed dropout prediction model techniques was classified into the risk group and the normal group using statistical methods and Naive Bays algorithm. And the intelligence dropout prediction system was constructed by applying the proposed dropout prediction model. We expect the proposed study would be used effectively to reduce the students dropout in university.

SEISMIC RESPONSE OF MULTISTORY BUILDING STRUCTURES WITH FLEXIBLE FLOOR DIAPHRNGMS

  • Lee, Dong-Guen;Moon, Sung-Kwon
    • Computational Structural Engineering
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    • v.2 no.1
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    • pp.47-53
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    • 1989
  • An efficient model for three-dimensional analysis of multistory structures with flexible floor diaphrgms is proposed in this paper. Three-dimensional analysis of a building structure using a finite element model requires tedious input data preparation, longer computation time, and larger computer memory. The model proposed in this study is developed by assembling a series of two-dimensional resisting systems and is considered to overcome the shortcomings of a three-dimensional finite element model without deteriorating the accuracy of analysis results. Static and dynamic analysis results obtained using the proposed model are in excellent agreement with those obtained using three-dimensional finite element models in terms of displacement, periods, and mode shapes. Effects of floor diaphragm flexibility on seismic response of multistory building structures are investigated.

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Active Shape Model-based Object Tracking using Depth Sensor (깊이 센서를 이용한 능동형태모델 기반의 객체 추적 방법)

  • Jung, Hun Jo;Lee, Dong Eun
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.9 no.1
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    • pp.141-150
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    • 2013
  • This study proposes technology using Active Shape Model to track the object separating it by depth-sensors. Unlike the common visual camera, the depth-sensor is not affected by the intensity of illumination, and therefore a more robust object can be extracted. The proposed algorithm removes the horizontal component from the information of the initial depth map and separates the object using the vertical component. In addition, it is also a more efficient morphology, and labeling to perform image correction and object extraction. By applying Active Shape Model to the information of an extracted object, it can track the object more robustly. Active Shape Model has a robust feature-to-object occlusion phenomenon. In comparison to visual camera-based object tracking algorithms, the proposed technology, using the existing depth of the sensor, is more efficient and robust at object tracking. Experimental results, show that the proposed ASM-based algorithm using depth sensor can robustly track objects in real-time.

Profile Position Control of Reactive Batch Distillation Column (회분식 반응 증류탑의 프로필 위치 제어)

  • Im, Chae-Yong;Han, Myeong-Wan
    • Journal of Institute of Control, Robotics and Systems
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    • v.7 no.3
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    • pp.263-268
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    • 2001
  • A new control scheme s proposed for the control of reactive batch distillation (RBD) column. A nonlinear wave model captures the essential dynamic behavior of the RBD process. The proposed control scheme is based on both Generic Model Control(GNC) and nonlinear wave model. The control scheme uses a profile position of the column as a controlled variable. Ethanol esterification process using RBD is chosen as an example process. Tight control of the distillate purity is obtained with the use of the proposed control scheme.

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Prediction of Compressive Strength of Concretes Containing Silica Fume and Styrene-Butadiene Rubber (SBR) with a Mathematical Model

  • Shafieyzadeh, M.
    • International Journal of Concrete Structures and Materials
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    • v.7 no.4
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    • pp.295-301
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    • 2013
  • This paper deals with the interfacial effects of silica fume (SF) and styrene-butadiene rubber (SBR) on compressive strength of concrete. Analyzing the compressive strength results of 32 concrete mixes performed over two water-binder ratios (0.35, 0.45), four percentages replacement of SF (0, 5, 7.5, and 10 %) and four percentages of SBR (0, 5, 10, and 15 %) were investigated. The results of the experiments were showed that in 5 % of SBR, compressive strength rises slightly, but when the polymer/binder materials ratio increases, compressive strength of concrete decreases. A mathematical model based on Abrams' law has been proposed for evaluation strength of SF-SBR concretes. The proposed model provides the opportunity to predict the compressive strength based on time of curing in water (t), and water, SF and SBR to binder materials ratios that they are shown with (w/b), (s) and (p).This understanding model might serve as useful guides for commixture concrete admixtures containing of SF and SBR. The accuracy of the proposed model is investigated. Good agreements between them are observed.

Document Classification Model Using Web Documents for Balancing Training Corpus Size per Category

  • Park, So-Young;Chang, Juno;Kihl, Taesuk
    • Journal of information and communication convergence engineering
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    • v.11 no.4
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    • pp.268-273
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    • 2013
  • In this paper, we propose a document classification model using Web documents as a part of the training corpus in order to resolve the imbalance of the training corpus size per category. For the purpose of retrieving the Web documents closely related to each category, the proposed document classification model calculates the matching score between word features and each category, and generates a Web search query by combining the higher-ranked word features and the category title. Then, the proposed document classification model sends each combined query to the open application programming interface of the Web search engine, and receives the snippet results retrieved from the Web search engine. Finally, the proposed document classification model adds these snippet results as Web documents to the training corpus. Experimental results show that the method that considers the balance of the training corpus size per category exhibits better performance in some categories with small training sets.

Stable PID Tuning for High-order Integrating Processes using Model Reduction Method (모델축소를 이용한 고차계 적분공정의 안정한 PID 동조)

  • Lee, Won-Hyok;Hwang, Hyung-Soo
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.56 no.11
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    • pp.2010-2016
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    • 2007
  • PID control is windely used to control stable processes, However, its application to integrating processes is less common. In this paper, we proposed a stable PID controller tuning method for integrating processes with time delay using model reduction method. For proposed model reduction method, it disconnect an integrating factor from integrating processes and reduces separate process using reduction method. and it connect an integrating factor to reduced model. We can obtain stable integrating processes using P controller in inner feedback loop and PID tuning is then used to cancel the pole of the feedback loop. This guarantees both robustness and performance. Simulation examples are given to show the good performance of the proposed tuning method comparing with other methods.

A Study on the Efficient Finite Element Technique using Geometrical Symmetry (형상의 대칭성을 이용한 효율적인 3차원 유한요소 해석 기법에 관한 연구)

  • Im, Chang-Hwan;Kim, Hong-Gyu;Lee, Seok-Hui;Jeong, Hyeon-Gyo
    • The Transactions of the Korean Institute of Electrical Engineers B
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    • v.49 no.7
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    • pp.462-467
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    • 2000
  • In general, when geometry and current distribution have a periodic or symmetric property, the analysis of a part model is sufficient to represent that of a whole model by using the periodic boundary condition. It is impossible, however, to apply the periodic boundary condition when the current distribution is not symmetric even if the geometry of the model is symmetric. In this paper, a novel technique to resolve this problem is proposed. Even when the geometry is symmetric and the current distribution is not, the proposed method enables that calculation time for a whole model is reduced to that for a part model. The proposed method is applied to a deflection yoke (DY), and validness and efficiency of the method are verified.

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The Identification of Multi-Fuzzy Model by means of HCM and Genetic Algorithms (클러스터링 기법과 유전자 알고리즘에 의한 다중 퍼지 모델으 동정)

  • Park, Byoun-Jun;Lee, Su-Gu;Oh, Sung-Kwun;Kim, Hyun-Ki
    • Proceedings of the KIEE Conference
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    • 2000.07d
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    • pp.3007-3009
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    • 2000
  • In this paper, we design a Multi-Fuzzy model by means of clustering method and genetic algorithms for a nonlinear system. In order to determine structure of the proposed Multi-Fuzzy model. HCM clustering method is used. The parameters of membership function of the Multi-Fuzzy are identified by genetic algorithms. We use simplified inference and linear inference as inference method of the proposed Multi-Fuzzy model and the standard least square method for estimating consequence parameters of the Multi-Fuzzy. Finally, we use some of numerical data to evaluate the proposed Multi-Fuzzy model and discuss about the usefulness.

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