• Title/Summary/Keyword: Intelligent View Model

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Fuzzy Cognitive Maps built in NI LabVIEW for control of dynamic process (NI LabVIEW를 이용한 동적 제어용 FCM 제어기)

  • Balashov, Vadim S.;Skatova, Darya D.;Choe, Seong-Ju;Jo, Hyeon-Chan
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2007.04a
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    • pp.217-220
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    • 2007
  • This paper studies method of controlling dynamic process with Fuzzy Cognitive Map (FCM) built in NI LabVIEW software. FCM is the hybrid methodology that combines fuzzy logic and neural networks. A FCM will be developed using NI LabVIEW software to model and control a process of dynamic system. Nowadays more autonomous and intelligent systems are very useful in many areas of people lives especially related with Complex Systems.

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A Reduction Method of Search Space for Polyhedral Object Recognition (다면체 인식을 위한 탐색 공간 감소 기법)

  • Lee, Sang-Yong
    • Journal of the Korean Institute of Intelligent Systems
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    • v.13 no.4
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    • pp.381-385
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    • 2003
  • We suggest a method which reduces the search space of a model-base on multiple-view approach for polyhedral object recognition using the ART-1 neural network. In this approach, the model-base is consisted of extracted features from two-dimensional projections observed at the predetermined viewpoints of a viewing sphere enclosing the object.

General problem solver를 이용한 intelligent LP 모형화에 대한 연구

  • 박성주;권오병
    • Proceedings of the Korean Operations and Management Science Society Conference
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    • 1991.10a
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    • pp.469-474
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    • 1991
  • Recent interests in intelligent LP modeling aim to support MS/OR-naive users to be able to apply LP models to practical problems without the expert knowledges required. For more generalized LP modeling, a GPS(General Problem Solver)-based approach is suggested in this paper. It identifies modeling process as a means-ends analysis process. In view of this approach, a) we first divide the knowledges into domain specific assertive knowledges(state) and procedural knowledges about LP modeling(operator and macro) for model-domain independence, b) and then generate LP model according to the difference resolution techniques.

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Robot Control integrating LabVIEW and Matlab

  • Balashov, V.S.;Skatova, D.D.;Choi, S.J.
    • Proceedings of the KAIS Fall Conference
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    • 2007.05a
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    • pp.249-252
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    • 2007
  • This study shows possibility of Matlab and LabVIEW integration for controlling of robot's manipulator. Examined approach can be used for control of complex system with intelligent control capability. Instance of Robotic System controller is described in details. Structure of control system is divided into three parts Virtual Instrument of LabVIEW, MatLab Script for solving and Matlab Simulink model for visualizing, which are explained separately. In addition, used neglects are explained and founded.

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Hull Form Generation by Using Fuzzy Model

  • Lee, Yeon-Seung-;Jeong, Seong-Jae;Kim, Su-Young-;Geuntaek-Kang
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 1993.06a
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    • pp.1234-1237
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    • 1993
  • This paper discusses the hull form generation from fuzzy model constructed with actual ship data using fuzzy concept. SAC, which is the most important factor in the hull form generation, is expressed by a fuzzy model describing the relationships among design parameters, which have a great influence on SAC, through model identification process with the actual ship data and design parameters. Then, we can infer the SAC of an aimed ship through the process of fuzzy inference and decide the offset of a front view by making the fuzzy model between SAC and offset as well. In conclusion, this paper makes a step forward from the geometrical definition, which has been used for hull form generation so far, to direct mathematical formulae about the relationship between design parameters and offset. So, if the design parameters are given, we can generate the hull form taking such properties into account.

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Balancing Control of a Single-wheel Mobile Robot from a Stick-Model Point of View (스틱 모델 관점에서의 외바퀴 로봇 밸런싱 제어)

  • Lee, Sang-Deok;Jung, Seul
    • Proceedings of the KIEE Conference
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    • 2015.07a
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    • pp.1327-1328
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    • 2015
  • 본 논문에서는 스틱 모델을 사용하여 외바퀴 로봇의 수직 방향에서 생기는 파라메트릭 진동을 시뮬레이션 분석하고, 분석된 결과를 바탕으로 제어 법칙을 유도한 다음, 실험을 통해 성능을 검증한다. 실험에 활용된 외바퀴 로봇은 수평 방향에 대해서는 비례미분제어기를 사용하고, 수직 방향에 대해서는 진동제어기를 활용한다.

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Optimal Economical Running Patterns Based on Fuzzy Model (철도차량을 위한 퍼지모델기반 최적 경제운전 패턴 개발)

  • Lee, Tae-Hyung;Hwang, Hee-Soo
    • Journal of the Korean Institute of Intelligent Systems
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    • v.16 no.5
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    • pp.594-600
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    • 2006
  • The optimization has been performed to search an economical running pattern in the view point of trip time and energy consumption. Fuzzy control model has been applied to build the meta-model. To identify the structure and its parameters of a fuzzy model, fuzzy c-means clustering method and differential evolutionary scheme ate utilized, respectively. As a result, two meta-models for trip time and energy consumption are constructed. The optimization to search an economical running pattern is achieved by differential evolutionary scheme. The result shows that the proposed methodology is very efficient and conveniently applicable to the operation of railway system.

Robo-Advisor Algorithm with Intelligent View Model (지능형 전망모형을 결합한 로보어드바이저 알고리즘)

  • Kim, Sunwoong
    • Journal of Intelligence and Information Systems
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    • v.25 no.2
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    • pp.39-55
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    • 2019
  • Recently banks and large financial institutions have introduced lots of Robo-Advisor products. Robo-Advisor is a Robot to produce the optimal asset allocation portfolio for investors by using the financial engineering algorithms without any human intervention. Since the first introduction in Wall Street in 2008, the market size has grown to 60 billion dollars and is expected to expand to 2,000 billion dollars by 2020. Since Robo-Advisor algorithms suggest asset allocation output to investors, mathematical or statistical asset allocation strategies are applied. Mean variance optimization model developed by Markowitz is the typical asset allocation model. The model is a simple but quite intuitive portfolio strategy. For example, assets are allocated in order to minimize the risk on the portfolio while maximizing the expected return on the portfolio using optimization techniques. Despite its theoretical background, both academics and practitioners find that the standard mean variance optimization portfolio is very sensitive to the expected returns calculated by past price data. Corner solutions are often found to be allocated only to a few assets. The Black-Litterman Optimization model overcomes these problems by choosing a neutral Capital Asset Pricing Model equilibrium point. Implied equilibrium returns of each asset are derived from equilibrium market portfolio through reverse optimization. The Black-Litterman model uses a Bayesian approach to combine the subjective views on the price forecast of one or more assets with implied equilibrium returns, resulting a new estimates of risk and expected returns. These new estimates can produce optimal portfolio by the well-known Markowitz mean-variance optimization algorithm. If the investor does not have any views on his asset classes, the Black-Litterman optimization model produce the same portfolio as the market portfolio. What if the subjective views are incorrect? A survey on reports of stocks performance recommended by securities analysts show very poor results. Therefore the incorrect views combined with implied equilibrium returns may produce very poor portfolio output to the Black-Litterman model users. This paper suggests an objective investor views model based on Support Vector Machines(SVM), which have showed good performance results in stock price forecasting. SVM is a discriminative classifier defined by a separating hyper plane. The linear, radial basis and polynomial kernel functions are used to learn the hyper planes. Input variables for the SVM are returns, standard deviations, Stochastics %K and price parity degree for each asset class. SVM output returns expected stock price movements and their probabilities, which are used as input variables in the intelligent views model. The stock price movements are categorized by three phases; down, neutral and up. The expected stock returns make P matrix and their probability results are used in Q matrix. Implied equilibrium returns vector is combined with the intelligent views matrix, resulting the Black-Litterman optimal portfolio. For comparisons, Markowitz mean-variance optimization model and risk parity model are used. The value weighted market portfolio and equal weighted market portfolio are used as benchmark indexes. We collect the 8 KOSPI 200 sector indexes from January 2008 to December 2018 including 132 monthly index values. Training period is from 2008 to 2015 and testing period is from 2016 to 2018. Our suggested intelligent view model combined with implied equilibrium returns produced the optimal Black-Litterman portfolio. The out of sample period portfolio showed better performance compared with the well-known Markowitz mean-variance optimization portfolio, risk parity portfolio and market portfolio. The total return from 3 year-period Black-Litterman portfolio records 6.4%, which is the highest value. The maximum draw down is -20.8%, which is also the lowest value. Sharpe Ratio shows the highest value, 0.17. It measures the return to risk ratio. Overall, our suggested view model shows the possibility of replacing subjective analysts's views with objective view model for practitioners to apply the Robo-Advisor asset allocation algorithms in the real trading fields.

The network model for Detection Systems based on data mining and the false errors

  • Lee Se-Yul;Kim Yong-Soo
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.6 no.2
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    • pp.173-177
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    • 2006
  • This paper investigates the asymmetric costs of false errors to enhance the detection systems performance. The proposed method utilizes the network model to consider the cost ratio of false errors. By comparing false positive errors with false negative errors this scheme achieved better performance on the view point of both security and system performance objectives. The results of our empirical experiment show that the network model provides high accuracy in detection. In addition, the simulation results show that effectiveness of probe detection is enhanced by considering the costs of false errors.

A study on the bridge safety management model using Ubiquitous technology (유비쿼터스 기술을 이용한 교량 안전관리 방안 연구)

  • Jo, Byung-Wan;Kim, Do-Keun;No, Seung-Hyun;Kim, Heoun
    • 한국방재학회:학술대회논문집
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    • 2008.02a
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    • pp.489-492
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    • 2008
  • Nowadays in order to estimate safety diagnosis of bridge, a lot of data like static and dynamic displacement, accelerometer, wind velocity and so on are demanded. When it comes to measure these data, cabled sensor is essential equipment. But cabled sensors have also inefficient factors. From this point of view, considering practical aspects of using these expensive equipments which have been used to examine safety diagnosis, measuring by cabled sensors is restrictive in some respect. Recently to improve theses problems, Wireless sensor system was introduced. But this system can't perform intelligent reaction because database of this system is just based on internet. In this paper, the intelligent bridge safety management model which can be installed easily, measured at all times and dealing intelligently with various situations is developed to improve these problems.

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