• 제목/요약/키워드: state sets

검색결과 449건 처리시간 0.035초

Comparison of Asset Management Approaches to Optimize Navigable Waterway Infrastructure

  • Oni, Bukola;Madson, Katherine;MacKenzie, Cameron
    • 국제학술발표논문집
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    • The 9th International Conference on Construction Engineering and Project Management
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    • pp.3-10
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    • 2022
  • An estimated investment gap of $176 billion needs to be filled over the next ten years to improve America's inland waterway transportation systems. Many of these infrastructure systems are now beyond their original 50-year design life and are often behind in maintenance due to funding constraints. Therefore, long-term maintenance strategies (i.e., asset management (AM) strategies) are needed to optimize investments across these waterway systems to improve their condition. Two common AM strategies include policy-driven maintenance and performance-driven maintenance. Currently, limited research exists on selecting the optimal AM approach for managing inland waterway transportation assets. Therefore, the goal of this study is to provide a decision model that can be used to select the optimal alternative between the two AM approaches by considering key uncertainties such as asset condition, asset test results, and asset failure. We achieve this goal by addressing the decision problem as a single-criterion problem, which calculates each alternative's expected value and certain equivalence using allocated monetary values to determine the recommended alternative for optimally maintaining navigable waterways. The decision model considers estimated and predicted values based on the current state of the infrastructure. This research concludes that the performance-based approach is the optimal alternative based on the expected value obtained from the analysis. This research sets the stage for further studies on fiscal constraints that will effectively optimize these assets condition.

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EXTREME PRESERVERS OF TERM RANK INEQUALITIES OVER NONBINARY BOOLEAN SEMIRING

  • Beasley, LeRoy B.;Heo, Seong-Hee;Song, Seok-Zun
    • 대한수학회지
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    • 제51권1호
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    • pp.113-123
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    • 2014
  • The term rank of a matrix A over a semiring $\mathcal{S}$ is the least number of lines (rows or columns) needed to include all the nonzero entries in A. In this paper, we characterize linear operators that preserve the sets of matrix ordered pairs which satisfy extremal properties with respect to term rank inequalities of matrices over nonbinary Boolean semirings.

MULTIPLE VALUED ITERATIVE DYNAMICS MODELS OF NONLINEAR DISCRETE-TIME CONTROL DYNAMICAL SYSTEMS WITH DISTURBANCE

  • Kahng, Byungik
    • 대한수학회지
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    • 제50권1호
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    • pp.17-39
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    • 2013
  • The study of nonlinear discrete-time control dynamical systems with disturbance is an important topic in control theory. In this paper, we concentrate our efforts to multiple valued iterative dynamical systems, which model the nonlinear discrete-time control dynamical systems with disturbance. After establishing the validity of such modeling, we study the invariant set theory of the multiple valued iterative dynamical systems, including the controllability/reachablity problems of the maximal invariant sets.

Self-Organized Reinforcement Learning Using Fuzzy Inference for Stochastic Gradient Ascent Method

  • K, K.-Wong;Akio, Katuki
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2001년도 ICCAS
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    • pp.96.3-96
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    • 2001
  • In this paper the self-organized and fuzzy inference used stochastic gradient ascent method is proposed. Fuzzy rule and fuzzy set increase as occasion demands autonomously according to the observation information. And two rules(or two fuzzy sets)becoming to be similar each other as progress of learning are unified. This unification causes the reduction of a number of parameters and learning time. Using fuzzy inference and making a rule with an appropriate state division, our proposed method makes it possible to construct a robust reinforcement learning system.

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Estimation of the General Along-Track Acceleration in the KOMPSAT-1 Orbit Determination

  • Lee, Byoung-Sun;Lee, Jeong-Sook;Kim, Jae-Hoon
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2001년도 ICCAS
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    • pp.92.4-92
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    • 2001
  • Estimation of the general along-track acceleration was performed in the KOMPSAT-1 orbit determination process. Several sets of the atmospheric drag and solar radiation pressure coefficients were also derived with the different spacecraft area. State vectors in the orbit determination with the different spacecraft area were compared in the time frame. The orbit prediction using the estimated coefficients was performed and compared with the orbit determination results. The orbit prediction with the different general acceleration values was also carried out for the comparison.

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빅데이터 천문학 : PySpark를 이용한 천문자료 분석 (Big Data Astronomy : Let's "PySpark" the Universe)

  • Hong, Sungryong
    • 천문학회보
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    • 제43권1호
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    • pp.63.1-63.1
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    • 2018
  • The modern large-scale surveys and state-of-the-art cosmological simulations produce various kinds of big data composed of millions and billions of galaxies. Inevitably, we need to adopt modern Big Data platforms to properly handle such large-scale data sets. In my talk, I will briefly introduce the de facto standard of modern Big Data platform, Apache Spark, and present some examples to demonstrate how Apache Spark can be utilized for solving data-driven astronomical problems.

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간략화된 트롤 시스템의 퍼지제어 (Fuzzy Logic Control for a Simplified Trawl System)

  • 이춘우
    • 수산해양기술연구
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    • 제30권3호
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    • pp.189-198
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    • 1994
  • This paper describes the model of a simplified trawl system and a control method by using fuzzy algorithm in controlling the depth of trawl gear. Fuzzy logic control rules are sets of linguistic expression that are used by an experienced performer in real operation. For real time processing of the control rules, the look-up tables are used. Computer simulation results indicate that the proposed fuzzy controller shows fast response with minimum steady-state error and robustness properties to the simulated disturbance.

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퍼지제어 시스템을 위한 이득동조 방법 (Scaling Factor Tuning Method for Fuzzy Control System)

  • 최한수;김성중
    • 대한전기학회논문지
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    • 제43권5호
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    • pp.819-826
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    • 1994
  • This paper deals with a self-tuning fuzzy controller. The fuzzy controller is constructed with linguistic rules which consist of the fuzzy sets. Each fuzzy set is characterized by a membership function. The tuning fuzzy controller has paramenters that are input/output scaling factors to effect control output. In this paper we propose a tuning method for the scaling factor Computer simulations carried out on first-order and second-order processes will show how the present tuning approach improves the transient and the steady-state characteristics of the overall system.The applicability of the proposed algorithm is certified by computer simulation results.

DISKCYCLIC C0-SEMIGROUPS AND DISKCYCLICITY CRITERIA

  • Moosapoor, Mansooreh
    • Nonlinear Functional Analysis and Applications
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    • 제27권1호
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    • pp.111-119
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    • 2022
  • In this article, we prove that diskcyclic C0-semigroups exist on any infinite-dimensional Banach space. We show that a C0-semigroup (Tt)t≥0 satisfies the diskcyclicity criterion if and only if any of Tt's satisfies the diskcyclicity criterion for operators. Moreover, we show that there are diskcyclic C0-semigroups that do not satisfy the diskcyclicity criterion. Also, we state various criteria for diskcyclicity of C0-semigroups based on dense sets and d-dense orbits.

확률변수를 이용한 음악에 따른 감정분석에의 최적 EEG 채널 선택 (A Selection of Optimal EEG Channel for Emotion Analysis According to Music Listening using Stochastic Variables)

  • 변성우;이소민;이석필
    • 전기학회논문지
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    • 제62권11호
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    • pp.1598-1603
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    • 2013
  • Recently, researches on analyzing relationship between the state of emotion and musical stimuli are increasing. In many previous works, data sets from all extracted channels are used for pattern classification. But these methods have problems in computational complexity and inaccuracy. This paper proposes a selection of optimal EEG channel to reflect the state of emotion efficiently according to music listening by analyzing stochastic feature vectors. This makes EEG pattern classification relatively simple by reducing the number of dataset to process.