• Title/Summary/Keyword: Uncertain Dynamic Systems

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Goal-oriented Geometric Model Based Intelligent System Architecture for Adaptive Robotic Motion Generation in Dynamic Environment

  • Lee, Dong-Hun;Hwang, Kyung-Hun;Chung, Chae-Wook;Kuc, Tae-Yong
    • 제어로봇시스템학회:학술대회논문집
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    • 2005.06a
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    • pp.2568-2574
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    • 2005
  • Control architecture of the action based robot engineering can be divided into two types of deliberate type - and reactive type- controller. Typical deliberate type, slow in reaction speed, is well suited for the realization of the higher intelligence with its capability to forecast on the basis of environmental model according to time flow, while reactive type is suitable for the lower intelligence as it fits to the realization of speedy reactive action by inputting the sensor without a complete environmental model. Looking at the environments in the application areas in which robots are actually used, we can see that they have been mostly covered by the uncertain and unknown dynamic changes depending on time and place, the previously known knowledge being existed though. It may cause, therefore, any deterioration of the robot performance as well as further happen such cases as the robots can not carry out their desired performances, when any one of these two types is solely engaged. Accordingly this paper aims at suggesting Goal-oriented Geometric Model(GGM) Based Intelligent System Architecture which leads the actions of the robots to perform their jobs under variously changing environment and applying the suggested system structure to the navigation issues of the robots. When the robots do perform navigation in human life changing in a various manner with time, they can appropriately respond to the changing environment by doing the action with the recognition of the state. Extending this concept to cover the highest hierarchy without sticking only to the actions of the robots can lead us to apply to the algorithm to perform various small jobs required for the carrying-out of a large main job.

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Object Relationship Modeling based on Bayesian Network Integration for Improving Object Detection Performance of Service Robots (서비스 로봇의 물체 탐색 성능 향상을 위한 베이지안 네트워크 결합 기반 물체 관계 모델링)

  • Song Youn-Suk;Cho Sung-Bae
    • Journal of the Korean Institute of Intelligent Systems
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    • v.15 no.7
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    • pp.817-822
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    • 2005
  • Recently tile study that exploits visual information for tile services of robot in indoor environments is active. Conventional image processing approaches are based on the pre-defined geometric models, so their performances are likely to decrease when they are applied to the uncertain and dynamic environments. For this, diverse researches to manage the uncertainty based on the knowledge for improving image recognition performance have been doing. In this paper we propose a Bayesian network modeling method for predicting the existence of target objects when they are occluded by other ones for improving the object detection performance of the service robots. The proposed method makes object relationship, so that it allows to predict the target object through observed ones. For this, we define the design method for small size Bayesian networks (primitive Bayesian netqork), and allow to integrate them following to the situations. The experiments are performed for verifying the performance of constructed model, and they shows $82.8\%$ of accuracy in 5 places.

Parametric Study on Earthquake Responses of Soil-structure Interaction System by Substructure Method (부분구조법에 의한 지반-구조물상호작용시스템의 지진응답 매개변수 연구)

  • 박형기;조양희
    • Journal of the Earthquake Engineering Society of Korea
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    • v.2 no.1
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    • pp.1-10
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    • 1998
  • In the dynamic soil-structure interaction(SSI) analysis, numerous uncertain parameters are involved. They include the uncertainties in the definition of input motions, modeling of soil-structure interaction systems. analysis techniques, etc. This paper presents the results of parametric studies of the seismic responses of a reactor containment structure built on the viscoelastic layered soil. Among the numerous parameter, this study concentrates on the effects of definition point of the input motion, embedment of structure to the base soil, thickness of the top soil layer, and rigidity of the base soil. The substructure method using frequency independent impedances is adopted. The method is based on the mode superposition method in time domain using the composite modal damping values of th SSI system computed from the ratio of dissipated energy to the strain energy for each model. From the study results, the sensitivity of each parameter on the earthquake responses has been suggested for the practical application of the substructure method of SSI analysis.

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An efficient approach for model updating of a large-scale cable-stayed bridge using ambient vibration measurements combined with a hybrid metaheuristic search algorithm

  • Hoa, Tran N.;Khatir, S.;De Roeck, G.;Long, Nguyen N.;Thanh, Bui T.;Wahab, M. Abdel
    • Smart Structures and Systems
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    • v.25 no.4
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    • pp.487-499
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    • 2020
  • This paper proposes a novel approach to model updating for a large-scale cable-stayed bridge based on ambient vibration tests coupled with a hybrid metaheuristic search algorithm. Vibration measurements are carried out under excitation sources of passing vehicles and wind. Based on the measured structural dynamic characteristics, a finite element (FE) model is updated. For long-span bridges, ambient vibration test (AVT) is the most effective vibration testing technique because ambient excitation is freely available, whereas a forced vibration test (FVT) requires considerable efforts to install actuators such as shakers to produce measurable responses. Particle swarm optimization (PSO) is a famous metaheuristic algorithm applied successfully in numerous fields over the last decades. However, PSO has big drawbacks that may decrease its efficiency in tackling the optimization problems. A possible drawback of PSO is premature convergence leading to low convergence level, particularly in complicated multi-peak search issues. On the other hand, PSO not only depends crucially on the quality of initial populations, but also it is impossible to improve the quality of new generations. If the positions of initial particles are far from the global best, it may be difficult to seek the best solution. To overcome the drawbacks of PSO, we propose a hybrid algorithm combining GA with an improved PSO (HGAIPSO). Two striking characteristics of HGAIPSO are briefly described as follows: (1) because of possessing crossover and mutation operators, GA is applied to generate the initial elite populations and (2) those populations are then employed to seek the best solution based on the global search capacity of IPSO that can tackle the problem of premature convergence of PSO. The results show that HGAIPSO not only identifies uncertain parameters of the considered bridge accurately, but also outperforms than PSO, improved PSO (IPSO), and a combination of GA and PSO (HGAPSO) in terms of convergence level and accuracy.

Linkage of Hydrological Model and Machine Learning for Real-time Prediction of River Flood (수문모형과 기계학습을 연계한 실시간 하천홍수 예측)

  • Lee, Jae Yeong;Kim, Hyun Il;Han, Kun Yeun
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.40 no.3
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    • pp.303-314
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    • 2020
  • The hydrological characteristics of watersheds and hydraulic systems of urban and river floods are highly nonlinear and contain uncertain variables. Therefore, the predicted time series of rainfall-runoff data in flood analysis is not suitable for existing neural networks. To overcome the challenge of prediction, a NARX (Nonlinear Autoregressive Exogenous Model), which is a kind of recurrent dynamic neural network that maximizes the learning ability of a neural network, was applied to forecast a flood in real-time. At the same time, NARX has the characteristics of a time-delay neural network. In this study, a hydrological model was constructed for the Taehwa river basin, and the NARX time-delay parameter was adjusted 10 to 120 minutes. As a result, we found that precise prediction is possible as the time-delay parameter was increased by confirming that the NSE increased from 0.530 to 0.988 and the RMSE decreased from 379.9 ㎥/s to 16.1 ㎥/s. The machine learning technique with NARX will contribute to the accurate prediction of flow rate with an unexpected extreme flood condition.

Study of the Ecosystem Model of Magazine on Special Genre Focusing on Collaboration System within Magazine Firm, Community and Creative User (전문잡지의 생태계 모델 분석 - 잡지사·커뮤니티·사용자의 협업체계를 중심으로)

  • Chang, Yong Ho;Kong, Byoung-Hun;Jin Jeon, Eun-Young
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.15 no.8
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    • pp.4831-4843
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    • 2014
  • Magazines on specific genres have been operating collaborative, co-working and collective production systems for value maximization using an adaptation strategy on the dynamic, complex and uncertain value network of the magazine industry. The study used a case study method, and data collection was performed by observational research, depth interviews and survey research. The subjects of the study were 'magazine industry', 'magazine firm and community', and 'collaboration system within creative users'. According to the research results, the ecosystem of magazines on a specific genre has been evolving into an innovative value network system, which is combined with the magazine firm, community users and magazine platform. Second, the rapid introduction of smart device environment changes the way of the collaborating system, in which an action and interaction came out within the community, creative users and magazine firms. Third, the production agency shows strong action and interaction, which fits the magazine platform within the ecosystem of a magazine on a specific genre well. This model has a similar fractal structure to the game, publishing, drama, movie, comic, and animation contents industry, converging to an innovative technology-based-creative-industry.

A Study on Netwotk Effect by using System Dynamics Analysis: A Case of Cyworld (시스템 다이내믹스 기법을 이용한 네트워크 효과 분석: 싸이월드 사례)

  • Kim, Ga-Hye;Yang, Hee-Dong
    • Information Systems Review
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    • v.11 no.1
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    • pp.161-179
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    • 2009
  • Nowadays an increasing number of Internet users are running individual websites as Blog or Cyworld. As this type of personal media has a great influence on communication among people, business comes to care about Network Effect, Network Software, and Social Network. For instance, Cyworld created the web service called 'Minihompy' for individual web-logs, and acquired 2.4milion users in 2007. Although many people assumed that the popularity of Minihompy, or Blog would be a passing fad, Cyworld has improved its service, and expanded its Network with various contents. This kind of expansion reflects survival efforts from infinite competitions among ISPs (Internet Service Provider) with focus on enhancing usability to users. However, Cyworld's Network Effect is gradually diminished in these days. Both of low production cost of service vendors and the low searching/conversing costs of users combine to make ISPs hard to keep their market share sustainable. To overcome this lackluster trend, Cyworld has adopted new strategies and try to lock their users in their service. Various efforts to improve the continuance and expansion of Network effect remain unclear and uncertain. If we understand beforehand how a service would improve Network effect, and which service could bring more effect, ISPs can get substantial help in launching their new business strategy. Regardless many diverse ideas to increase their user's duration online ISPs cannot guarantee 'how the new service strategies will end up in profitability. Therefore, this research studies about Network effect of Cyworld's 'Minihompy' using System-Dynamics method which could analyze dynamic relation between users and ISPs. Furthermore, the research aims to predict changes of Network Effect based on the strategy of new service. 'Page View' and 'Duration Time' can be enhanced for the short tenn because they enhance the service functionality. However, these services cannot increase the Network in the long-run. Limitations of this research include that we predict the future merely based on the limited data. We also limit the independent variables over Network Effect only to the following two issues: Increasing the number of users and increasing the Service Functionality. Despite of some limitations, this study perhaps gives some insights to the policy makers or others facing the stiff competition in the network business.