• 제목/요약/키워드: Logical Approach

검색결과 296건 처리시간 0.032초

제약조건이 있는 시뮬레이션을 위한 계층적 모델링 방법론 (Hierarchical Modeling Methodology for Contraint Simulations)

  • 이강선
    • 한국시뮬레이션학회논문지
    • /
    • 제9권4호
    • /
    • pp.41-50
    • /
    • 2000
  • We have many simulation constraints to meet as a modeled system becomes large and complex. Real-time simulations are the examples in that they are constrained by certain non-function constraints (e.g., timing constraints). In this paper, an enhanced hierarchical modeling methodology is proposed to efficiently deal with constraint-simulations. The proposed modeling method enhances hierarchical modeling methods to provide multi-resolution model. A simulation model is composed by determining the optimal level of abstraction that is guaranteed to meet the given simulation constraints. Four modeling activities are defined in the proposed method: 1) Perform the logical architectural design activity to produce a multi-resolution model, 2) Organize abstraction information of the multi-resolution model with AT (Abstraction Tree) structure, 3) Formulate the given constraints based on U (Integer Programming) approach and embrace the constraints to AT, and 4) Compose a model based on the determined level of abstraction with which the multi-resolution model can satisfy all given simulation constraints. By systematically handling simulation constraints while minimizing the modeler's interventions, we provide an efficient modeling environment for constraint-simulations.

  • PDF

AHP와 ANP를 이용한 기술기여도에 관한 연구 (A study on the degree of influence of technology by AHP and ANP)

  • 홍두화;정민용
    • 대한안전경영과학회지
    • /
    • 제8권4호
    • /
    • pp.167-180
    • /
    • 2006
  • The ANP(Analytic Network Process), though based on the AHP(Analytic Hierarchy Process), is a system for the analysis, synthesis, and justification of complex decisions with the capability to model non-linear relations between the elements. ANP allows the decision makers to leap beyond the traditional hierarchy to the interdependent environment of network modeling. The ANP is designed for problems characterized by the added complexity of interdependencies such as feedback and dependencies among problem elements. Using a network approach makes it possible to represent and analyze interactions, incorporate non-linear relations between the elements, and synthesize mutual effects by a single logical procedure. This study intends to evaluate the contribution of technology in intangible assets by the AHP and ANP.

Context Aware System based on Bayesian Network driven Context Reasoning and Ontology Context Modeling

  • Ko, Kwang-Eun;Sim, Kwee-Bo
    • International Journal of Fuzzy Logic and Intelligent Systems
    • /
    • 제8권4호
    • /
    • pp.254-259
    • /
    • 2008
  • Uncertainty of result of context awareness always exists in any context-awareness computing. This falling-off in accuracy of context awareness result is mostly caused by the imperfectness and incompleteness of sensed data, because of this reasons, we must improve the accuracy of context awareness. In this article, we propose a novel approach to model the uncertain context by using ontology and context reasoning method based on Bayesian Network. Our context aware processing is divided into two parts; context modeling and context reasoning. The context modeling is based on ontology for facilitating knowledge reuse and sharing. The ontology facilitates the share and reuse of information over similar domains of not only the logical knowledge but also the uncertain knowledge. Also the ontology can be used to structure learning for Bayesian network. The context reasoning is based on Bayesian Networks for probabilistic inference to solve the uncertain reasoning in context-aware processing problem in a flexible and adaptive situation.

시스템 특성함수 기반 평균보상 TD(${\lambda}$) 학습을 통한 유한용량 Fab 스케줄링 근사화 (Capacitated Fab Scheduling Approximation using Average Reward TD(${\lambda}$) Learning based on System Feature Functions)

  • 최진영
    • 산업경영시스템학회지
    • /
    • 제34권4호
    • /
    • pp.189-196
    • /
    • 2011
  • In this paper, we propose a logical control-based actor-critic algorithm as an efficient approach for the approximation of the capacitated fab scheduling problem. We apply the average reward temporal-difference learning method for estimating the relative value functions of system states, while avoiding deadlock situation by Banker's algorithm. We consider the Intel mini-fab re-entrant line for the evaluation of the suggested algorithm and perform a numerical experiment by generating some sample system configurations randomly. We show that the suggested method has a prominent performance compared to other well-known heuristics.

A Sensorless PMDC Motor Speed Controller with a Logical Overcurrent Protection

  • Guerreiro, M.G.;Foito, D.;Cordeiro, A.
    • Journal of Power Electronics
    • /
    • 제13권3호
    • /
    • pp.381-389
    • /
    • 2013
  • A method to control the speed or the torque of a permanent-magnet direct current motor is presented. The rotor speed and the external torque estimation are simultaneously provided by appropriate observers. The sensorless control scheme is based on current measurement and switching states of power devices. The observers performances are dependent on the accurate machine parameters knowledge. Sliding mode control approach was adopted for drive control, providing the suitable switching states to the chopper power devices. Despite the predictable chattering, a convenient first order switching function was considered enough to define the sliding surface and to correspond with the desired control specifications and drive performance. The experimental implementation was supported on a single dsPIC and the controller includes a logic overcurrent protection.

이산 시스템에서 샘플링 시간의 설정 및 PID 계수 조정 (Determining of the Sampling Time and Adjusting PID Coefficients in a Discrete System)

  • 최군호
    • 반도체디스플레이기술학회지
    • /
    • 제16권4호
    • /
    • pp.46-51
    • /
    • 2017
  • Recent controller design techniques often discretize the target system and implement a discrete controller that is digitized to match the target system. When constructing such a discrete system, it is necessary to first determine the sampling time. The smaller the sampling time is, the more advantageous it can be made similar to the original system, but the cost is a problem when realizing such a configuration as hardware. On the other hand, the longer the time, the more different the system is from the original system, and eventually the control becomes impossible. In this paper, we consider the above problem and propose a more logical approach to determine the sampling time in the discrete system and investigate the relation with the differential controller. We also apply this process to a nonlinear system called ARAGO disc and verify its validity through computer simulation.

  • PDF

Identity-based Deniable Authenticated Encryption for E-voting Systems

  • Jin, Chunhua;Chen, Guanhua;Zhao, Jianyang;Gao, Shangbing;Yu, Changhui
    • KSII Transactions on Internet and Information Systems (TIIS)
    • /
    • 제13권6호
    • /
    • pp.3299-3315
    • /
    • 2019
  • Deniable authentication (DA) is a protocol in which a receiver can generate an authenticator that is probabilistically indistinguishable from a sender. DA can be applied in many scenarios that require user privacy protection. To enhance the security of DA, in this paper, we construct a new deniable authenticated encryption (DAE) scheme that realizes deniable authentication and confidentiality in a logical single step. Compared with existing approaches, our approach provides proof of security and is efficient in terms of performance analysis. Our scheme is in an identity-based environment; thus, it avoids the public key certificate-based public key infrastructure (PKI). Moreover, we provide an example that shows that our protocol is applicable for e-voting systems.

Machine learning-based categorization of source terms for risk assessment of nuclear power plants

  • Jin, Kyungho;Cho, Jaehyun;Kim, Sung-yeop
    • Nuclear Engineering and Technology
    • /
    • 제54권9호
    • /
    • pp.3336-3346
    • /
    • 2022
  • In general, a number of severe accident scenarios derived from Level 2 probabilistic safety assessment (PSA) are typically grouped into several categories to efficiently evaluate their potential impacts on the public with the assumption that scenarios within the same group have similar source term characteristics. To date, however, grouping by similar source terms has been completely reliant on qualitative methods such as logical trees or expert judgements. Recently, an exhaustive simulation approach has been developed to provide quantitative information on the source terms of a large number of severe accident scenarios. With this motivation, this paper proposes a machine learning-based categorization method based on exhaustive simulation for grouping scenarios with similar accident consequences. The proposed method employs clustering with an autoencoder for grouping unlabeled scenarios after dimensionality reductions and feature extractions from the source term data. To validate the suggested method, source term data for 658 severe accident scenarios were used. Results confirmed that the proposed method successfully characterized the severe accident scenarios with similar behavior more precisely than the conventional grouping method.

A SIMULATION APPROACH TO CONSTRUCTION MANAGEMENT EDUCATION

  • Muhammad Imran Ghatala ;Sang-Hoon Lee ;Lingguang Song
    • 국제학술발표논문집
    • /
    • The 1th International Conference on Construction Engineering and Project Management
    • /
    • pp.962-967
    • /
    • 2005
  • Construction management requires decision-making skills. Main approaches to training construction management students are: (1) analyzing sample situations involving decision-making; and (2) teaching logical decision-making procedures. The absence of 'pressure' factors in these approaches has significant impacts on the success of the training. The approaches also lack 'dynamic' effects that help create a spontaneous plan for construction projects where unforeseen changes and interruptions may occur. To minimize the adverse effects of the existing approaches, this paper proposes a framework for developing a web-based training system. The application is delivered as a game involving decision-making on the student's part in response to developments at the job-site, and where one student competes against another in an attempt to simulate a real-world scenario.

  • PDF

국방 AI 소요의 중복 최적화를 위한 AI 능력(Capability)의 역할 개념모델 연구 (A study on a conceptual model of AI Capability's role to optimize duplication of defense AI requirements)

  • 박승규;이중윤;이주연
    • 시스템엔지니어링학술지
    • /
    • 제19권1호
    • /
    • pp.91-106
    • /
    • 2023
  • Multidimensional efforts such as budgeting, organizing, and institutionalizing are being carried out for the adoption of defense AI. However, there is little interest in eliminating duplication of defense resources that may occur during the AI adoption. In this study, we propose a theoretical conceptual model to optimize duplication of AI technology that may occur during the AI adoption in the vast defense field. For a systematic approach, the JCA of the US DoD and system abstraction method are applied, and the IMO logical structure is used to decompose AI requirements and identify duplication. As a result of analyzing the effectiveness of our conceptual model through six example defense AI requirements, it was found that the amount of requirements of data and AI technologies could be reduced by up to 41.7% and 70%, respectively, and estimated costs could be reduced by up to 35.5%.