• Title/Summary/Keyword: Environment Uncertainty

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Nonlinearity-Compensation Extended Kalman Filter for Handling Unexpected Measurement Uncertainty in Process Tomography

  • Kim, Jeong-Hoon;Ijaz, Umer Zeeshan;Kim, Bong-Seok;Kim, Min-Chan;Kim, Sin;Kim, Kyung-Youn
    • 제어로봇시스템학회:학술대회논문집
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    • 2005.06a
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    • pp.1897-1902
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    • 2005
  • The objective of this paper is to estimate the concentration distribution in flow field inside the pipeline based on electrical impedance tomography. Special emphasis is given to the development of dynamic imaging technique for two-phase field undergoing a rapid transient change. Nonlinearity-compensation extended Kalman filter is employed to cope with unexpected measurement uncertainty. The nonlinearity-compensation extended Kalman filter compensates for the influence of measurement uncertainty and solves the instability of extended Kalman filter. Extensive computer simulations are carried out to show that nonlinearity-compensation extended Kalman filter has enhanced estimation performance especially in the unexpected measurement environment.

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AUV hull lines optimization with uncertainty parameters based on six sigma reliability design

  • Hou, Yuan hang;Liang, Xiao;Mu, Xu yang
    • International Journal of Naval Architecture and Ocean Engineering
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    • v.10 no.4
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    • pp.499-507
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    • 2018
  • Autonomous Underwater Vehicle (AUV), which are becoming more and more important in ocean exploitation tasks, needs energy conservation urgently when sailing the complex mission path in long time cruise. As hull lines optimization design becomes the key factor, which closely related with resistance, in AUV preliminary design stage, uncertainty parameters need to be considered seriously. In this research, Myring axial symmetry revolution body with parameterized expression is assumed as AUV hull lines, and its travelling resistance is obtained via modified DATCOM formula. The problems of AUV hull lines design for the minimum travelling resistance with uncertain parameters are studied. Based on reliability-based optimization design technology, Design For Six Sigma (DFSS) for high quality level is conducted, and is proved more reliability for the actual environment disturbance.

Efficient Supplier Selection with Uncertainty Using Monte Carlo DEA (몬테카를로 DEA를 이용한 불확실성을 고려한 효율적 공급자 선정)

  • Ha, Chunghun
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.38 no.1
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    • pp.83-89
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    • 2015
  • Selection of efficient supplier is a very important process as risk or uncertainty of a supply chain and its environment are increasing. Previous deterministic DEA and probabilistic DEAs are very limited to handle various types of risk and uncertainty. In this paper, I propose an improved probabilistic DEA which consists of two steps; Monte Carlo simulation and statistical decision making. The simulation results show that the proposed method is proper to distinguish supplier's performance and provide statistical decision background.

Unit Commitment of a GENCO Under the Competitive Environment Considering the Uncertainty of Market Prices (가격 불확실성을 고려한 발전사업자 기동정지계획)

  • 정정원
    • The Transactions of the Korean Institute of Electrical Engineers A
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    • v.52 no.4
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    • pp.234-239
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    • 2003
  • In recent decades, many countries have introduced competition in the electricity industry. Now, unit commitment becomes not a problem to be solved by a monopoly company but the one to be tackled by each generation company(GENCO). Its aim has been altered from the global cost minimization to the each GENCO's profit maximization. In this paper, the author proposes the scheme of unit commitment of a GENCO to maximize profit considering the uncertainty of market clearing price. The type of the assumed market is a uniform price market. A genetic algorithm is used for the maximization of the profit.

Multiple Slug and Pumping Tests for Quality Enhancement of Hydraulic Parameter Estimates (순간수위변화 및 양수시험을 통한 수리상수 추정의 문제점 분석)

  • 이진용;이강근;정형재;배광옥
    • Journal of the Korean Society of Groundwater Environment
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    • v.6 no.1
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    • pp.14-22
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    • 1999
  • Slug and pumping tests have been widely used to obtain hydraulic parameter estimates in the field. Although a variety of sources of error and uncertainty can be involved in the course of the test performance and data analysis, serious considerations on these sources are often neglected. In this study these various sources of error and uncertainty are analyzed or discussed using repeated slug and pumping test data and some guide lines are suggested to improve quality of parameter estimates from the slug and pumping tests.

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An Evaluation of Lot-sizing Rules under the Uncretainty of Demand and Lead Time

  • Hwang, Hark;Kim, Jae-Ho
    • Journal of Korean Institute of Industrial Engineers
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    • v.10 no.1
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    • pp.27-36
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    • 1984
  • This paper examines the influence of the uncertainty in demand and lead time on the relative performances of ten well-known single stage lot-sizing rules in a rolling schedule environment. Two other factors, coefficient of variation and time between orders, which may affect the performances of the rules are also considered. To compare the rules under an identical condition, 100% service level is set by introducing safety stocks. The effects of various factor levels are checked statistically by the pairwise t-test and the results show that the uncertainty of the environment has a strong influence on the performance of the rules.

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Fuzzy Logic Control With Predictive Neural Network

  • Jung, Sung-Hoon
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 1996.10a
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    • pp.285-289
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    • 1996
  • Fuzzy logic controllers have been shown better performance than conventional ones especially in highly nonlinear plants. These results are caused by the nonlinear fuzzy rules were not sufficient to cope with significant uncertainty of the plants and environment. Moreover, it is hard to make fuzzy rules consistent and complete. In this paper, we employed a predictive neural network to enhance the nonlinear inference capability. The predictive neural network generates predictive outputs of a controlled plant using the current and past outputs and current inputs. These predictive outputs are used in terms of fuzzy rules in fuzzy inferencing. From experiments, we found that the predictive term of fuzzy rules enhanced the inference capability of the controller. This predictive neural network can also help the controller cope with uncertainty of plants or environment by on-line learning.

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The Effect of the Factors of Introducing Information Technology on Non-Financial Performance

  • Lim, Kil-Jae;Yi, Seon-Gyu
    • Journal of the Korea Society of Computer and Information
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    • v.20 no.12
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    • pp.107-113
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    • 2015
  • This study analyzed the effect of the factors of introducing information technology(organizational and environmental characteristics) on non-financial performance. As detailed variables of each characteristic, the technical support/task force, users' IT capability, and education/training were used for the organizational characteristics while the degree of competition, external pressure, and uncertainty of environment were used for the environmental characteristics. In the results of the analysis, such factors like technical support/task force, users' IT capability, and education/training of the organizational characteristics had significant influence on non-financial performance. Also, factors such as degree of competition, external pressure, and uncertainty of environment of the environmental characteristics had significant influence on non-financial performance.

Field Validation of alternative extraction method for the determination of airborne MWFs (대체용매를 이용한 금속가공유 측정방법 타당성에 대한 현장평가)

  • Jeong, Jee Yeon;Paik, Nam Won
    • Journal of Korean Society of Occupational and Environmental Hygiene
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    • v.19 no.2
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    • pp.96-101
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    • 2009
  • The purpose of this study was to conduct the field validation of alternative method(ETM method) by using non-carcinogenic, and less toxic solvents than NIOSH (National Institute for Occupational Safety and Health) analytical method 5524 for measuring the airborne metalworking fluids in workplaces. We carried out the field validation test by using the exposure chamber, guaranteeing the air sampling homogeneously in a machining environment. The ETM mixed solvent presented the complete solubility of MWFs used in test field. Based on the field test data, the bias of the ETM method from reference method, NIOSH analytical method 5524, was from -7.0% to 5.1%. The overall uncertainty of the ETM nethod was 21.6%, which satisfied the NIOSH criteria for the sampling and analytical criteria.

Retrospective Air Quality Simulations of the TexAQS-II: Focused on Emissions Uncertainty

  • Lee, DaeGyun;Kim, Soontae;Kim, Hyuncheol;Ngan, Fong
    • Asian Journal of Atmospheric Environment
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    • v.8 no.4
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    • pp.212-224
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    • 2014
  • There are several studies on the effects of emissions of highly reactive volatile organic compounds (HRVOC) from the industrial sources in the Houston-Galveston-Brazoria (HGB) area on the high ozone events during the Texas Air Quality Study (TexAQS) in summer of 2000. They showed that the modeled atmosphere lacked reactivity to produce the observed high ozone event and suggested "imputation" of HRVOC emissions from the base inventory. Byun et al. (2007b) showed the imputed inventory leads to too high ethylene concentrations compared to the measurements at the chemical super sites but still too little aloft compared to the NOAA aircraft. The paper suggested that the lack of reactivity in the modeled Houston atmosphere must be corrected by targeted, and sometimes of episodic, increase of HRVOC emissions from the large sources such as flares in the Houston Ship Channel (HSC) distributed into the deeper level of the boundary layer. We performed retrospective meteorological and air quality modeling to achieve better air quality prediction of ozone by comparison with various chemical and meteorological measurements during the Texas Air Quality Study periods in August-September 2006 (TexA QS-II). After identifying several shortcomings of the forecast meteorological simulations and emissions inputs, we prepared new retrospective meteorological simulations and updated emissions inputs. We utilized assimilated MM5 inputs to achieve better meteorological simulations (detailed description of MM5 assimilation can be found in F. Ngan et al., 2012) and used them in this study for air quality simulations. Using the better predicted meteorological results, we focused on the emissions uncertainty in order to capture high peak ozone which occasionally happens in the HGB area. We described how the ozone predictions are affected by emissions uncertainty in the air quality simulations utilizing different emission inventories and adjustments.