• 한국환경과학회지
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• 제7권6호
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• pp.833-843
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• 1998

It is noted that the red tides and the oxygen-deficient water mass are extensively developed in Masan Bay during summer. The nutrients mass balance was calculated in Masan Bay, using the three-dimensional numerical hydrodynamic model and the material cycle model. The material cycle model was calibrated with the data obtained on the field of the study area in June 1993. The nutrients mass balance calculated by the combination of the residual currents and material cycle model results showed nutrients of surface and middle levels to be transported from the inner part to the outer part of Masan Bay, and nutrients of bottom level to be transported from outer part to inner part of Masan Bay. The uptake rate of DIN in the box A1(surface level of inner part) was found to be 337. 5mg/$m^3$ㆍday, the largest value in all 9 boxes and that of DIP was found to be 18.6mg/$m^3$ㆍday in box A1, and the regeneration rate of DIN was found to be 78.2mg/$m^3$ㆍday in the box A3(bottom level of inner part), and that of DIP was found to be 18.6mg/$m^3$ㆍday in box A1. The regenerations of DIN and DIP in the water column of the entire Bay were found to be 7.66ton/day and 760kg/day, respectively. And the releases of DIN and DIP from the sediments of the entire Bay were found to be 2.86ton/day and 634kg/day, respectively. The regeneration rate was 2.5 times as high as the release rate in DIN, and 1.2 times in DIP. The results of mass balance calculation showed not only the nutrients released from the sediments but the nutrients regenerated in water column to be important in the control and management of water quality in Masan Bay.

• 한국정밀공학회지
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• 제19권11호
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• pp.192-199
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• 2002

This paper demonstrates that hybrid neural-genetic multimodel parameter estimation algorithm can be applied to structured system Identification of electro-hydraulic servo system. This algorithm are consist of a recurrent incremental credit assignment (ICRA) neural network and a genetic algorithm. The ICRA neural network evaluates each member of a generation of model and genetic algorithm produces new generation of model. We manufactured electro-hydraulic servo system and the hybrid neural-genetic multimodel parameter estimation algorithm is applied to the task to find the parameter values(mass, damping coefficient, bulk modulus, spring coefficient) which minimize total square error.

• 제어로봇시스템학회논문지
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• 제9권6호
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• pp.442-447
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• 2003

This paper demonstrates that a modified hybrid neural-genetic multimodel parameter estimation algorithm can be applied to structured system identification of an electro-hydraulic servo system. This algorithm is consists of a recurrent incremental credit assignment(ICRA) neural network and a genetic algorithm. The ICRA neural network evaluates each member of a generation of model and genetic algorithm produces new generation of model. The modified hybrid neural-genetic multimodel parameter estimation algorithm is applied to an electro-hydraulic servo system the task to find the parameter values such as mass, damping coefficient, bulk modulus, spring coefficient and disturbance, which minimizes the total square error.

• 한국정밀공학회지
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• 제20권5호
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• pp.196-203
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• 2003

This paper demonstrates that an improved hybrid neural-genetic multimodel parameter estimation algorithm can be applied to the structured system identification of an electro-hydraulic servo system. This algorithm is consists of a recurrent incremental credit assignment (ICRA) neural network and a genetic algorithm, The ICRA neural network evaluates each member of a generation of model and the genetic algorithm produces new generation of model. We manufactured an electro-hydraulic servo system and the improved hybrid neural-genetic multimodel parameter estimation algorithm is applied to the task to find the parameter values, such as mass, damping coefficient, bulk modulus, spring coefficient and disturbance, which minimize total square error.

• 대한공업교육학회지
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• 제34권2호
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• pp.396-410
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• 2009

이 논문은 산업용 로봇의 모델링을 할 때 일어나는 불확실성을 측정하여, 이 불확실성이 야기하는 비선형 문제를 해결하는 데 필요한 정보를 얻는 데 목적이 있다. 우선 주어진 로봇모델에서 수학적 운동방정식을 유도하고, 불학실성의 물리적 현실에 가능한 가상모델을 접목하여 수학적 확장 모델을 세우고, 이를 바탕으로 불확실성을 측정 할 수 있는 관측자를 설계한다. 이 불확실성에는 모델링을 하기 어려운 모델링 오차, 중력, 마찰, 질량의 불균일 분포, 코리오리스 힘이 포함된다. 관측자와 관련된 조건들을 관측가능성 및 수렴 관계를 분석한다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권2호
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• pp.907-923
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• 2020

For the severe haze situation in the Beijing-Tianjin-Hebei region, conventional fine particulate matter (PM2.5) concentration prediction methods based on pollutant data face problems such as incomplete data, which may lead to poor prediction performance. Therefore, this paper proposes a method of predicting the PM2.5 concentration based on image analysis technology that combines image data, which can reflect the original weather conditions, with currently popular machine learning methods. First, based on local parameter estimation, autoregressive (AR) model analysis and local estimation of the increase in image blur, we extract features from the weather images using an approach inspired by free energy and a no-reference robust metric model. Next, we compare the coefficient energy and contrast difference of each pixel in the AR model and then use the percentages to calculate the image sharpness to derive the overall mass fraction. Furthermore, the results are compared. The relationship between residual value and PM2.5 concentration is fitted by generalized Gauss distribution (GGD) model. Finally, nonlinear mapping is performed via the wavelet neural network (WNN) method to obtain the PM2.5 concentration. Experimental results obtained on real data show that the proposed method offers an improved prediction accuracy and lower root mean square error (RMSE).

• 한국분무공학회지
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• 제25권4호
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• pp.178-187
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• 2020

The current emission regulations, US Tier-4 and EU Stage-V, are only able to satisfy the regulations when all currently mass-produced emission reduction technologies such as EGR, DOC, DPF, and SCR are applied. Therefore, in this study, for the application of the Urea-SCR system to non-road diesel engines, the database was established by measuring the NO, NO2 concentration and calculating the NO2/NOx ratio based on the catalyst temperature and exhaust mass flow rate. Also, based on the measured NO2/NOx ratio data, a mathematical model was proposed to predict the NO2/NOx ratio at SCR catalyst, and the suitability of the model was verified through steady-state and transient mode. As a result of comparing the NO2/NOx ratio measured at the DOC outlet under the steady-state condition to two model values separately, the R2 was 0.9811 for the 3D map model and 0.9303 for the mathematical model. And in the case of the NO2/NOx ratio measured at the DPF outlet, the R2 was 0.9797 for the 3D map model and 0.935 for the mathematical model. It was confirmed that the R2 with the model value of the 3D Map of the mathematical model in the transient mode is 0.957, which shows high reliability.

• 한국에너지공학회:학술대회논문집
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• 한국에너지공학회 1995년도 춘계학술발표회 초록집
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• pp.113-116
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• 1995

Simplified approach has been adopted for the prediction of the thermal behavior of CANDU reactor core during power transients. Based on the assumption that the ratio of mass flow rate for each core channel does not vary during the transient, quasy-steady state analysis technique is applied with predicted core inlet boundary conditions(total mass flow rate and specific enthalpy). For restricted transient case, the presented method shows functionally reasonable estimation of core thermal behavior which could be implemented in the fast running reactor simulation program.

• 한국환경과학회지
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• 제8권5호
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• pp.575-586
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• 1999

From the environmental aspects, primary productivity of phytoplankton plays the most improtant role in enhancement of marine culture oyster production. This study may be divided into two branches; one is estimation of maximum oyster meat production per unit facility(Carrying Capacity) under the present enviromental conditions in Kamak Bay, the other is improvement of carrying from increase of primary productivity by changing the environmental conditions that cause not ot form an unfavorable environment such as the formation of oxygen deficient water mass using the eco-hydrodynamic model. By simulation of three-dimensional hydrdynamic model and ecosystem model, the comparison between observed and computed data showed good agreement. The results of sensitivity analysis showed that phytoplankton maximum growth rate was the most important parameter for phytoplankton and dissolved oxygen. The estimation of mean primary productivity of Wonpo, Kamak, Pyongsa, and Kunnae culture grounds in Kamak Bay during culturing period were 3.73gC/$m^2$/d, 2.12gC/$m^2$/d, 1.98gC/$m^2$/d, and 1.26gC/$m^2$/d, respectively. Under condition not ot form the oxygen deficient water mass, four times increasing of pollutants loading as much as the present loading from river increased mean primary productivity of whole culture grounds to 4.02gC/$m^2$/d. Sediment N, P fluxes that allowed for 35% increasing from the present conditions increased mean primary productivity of whole culture grounds to 3.65gC/$m^2$/d. Finally, ten times increasing of boundary loadings from the present conditions increased mean primary productivity of whole culture grounds to 3.95gC/$m^2$/d. The maximum oyster meat production per year and that of unit facility in actual oyster culture grounds under the present conditions were 6,929ton and 0.93ton, respectively. This 0.93ton/unit facility is considered to be the carrying capacity in study area, and if the primary productivity is increased by changing the environmental conditions, oyster production can be increased.

• 제어로봇시스템학회논문지
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• 제14권9호
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• pp.886-892
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• 2008

In this paper, a closed-loop observer to extract the center of mass (CoM) of a bipedal robot is suggested. Comparing with the simple conversion method of just using joint angle measurements, it enables to get more reliable estimates by fusing both joint angle measurements and F/T sensor outputs at ankle joints. First, a nonlinear-type observer is constructed to estimate the flexible rotational motion of the biped in the extended Kalman filter framework. It adopts the flexible inverted pendulum model which is appropriate to address the flexible motion of bipeds, specifically in the single support phase. The predicted estimates of CoM in terms of the flexible motion observer are combined with measurements (that is, output of the CoM conversion equation with joint angles). Then, we have final CoM estimates depending on the weighting values which penalize the flexible motion model and the CoM conversion equation. Simulation results show the effectiveness of the proposed algorithm.