• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2006.05a
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• pp.121-124
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• 2006

본 논문에서는 Bacterial Foraging Algorithm과 FCM(fuzzy c-means)클러스터링을 이용하여 TSK(Takagi-Sugeno-Kang)형태의 퍼지 규칙 생성과 퍼지 시스템(FCM-ANFIS)을 효과적으로 구축하는 방법을 제안한다. 구조동정에서는 먼저 PCA(Principal Component Analysis)을 이용하여 입력 데이터 성분간의 상관관계를 제거한 후에 FCM을 이용하여 클러스터를 생성하고 성능지표에 근거해서 타당한 클러스터의 수, 즉 퍼지 규칙의 수를 얻는다. 파라미터 동정에서는 Bacterial Foraging Algorithm을 이용하여 전제부 파라미터를 최적화 시킨다. 결론부 파라미터는 RLSE(Recursive Least Square Estimate)에 의해 추정되어진다. PCA(Principal Component Analysis)와 FCM을 적용함으로써 타당한 규칙 수를 생성하였고 Bacterial Foraging Algorithm을 이용하여 최적의 전제부 파라미터를 구하였다. 제안된 방법의 성능을 평가하기 위하여 Box-Jenkins의 가스로 데이터와 Rice taste 데이터의 모델링에 적용하였고 우수한 성능을 보임을 알 수 있었다.

• Asian-Australasian Journal of Animal Sciences
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• v.1 no.3
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• pp.149-152
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• 1988

Postweaning performances of steer from 11 to 18 months of age under intensive feedlot condition were examined in Brahman and Santa Gertudis cattle breeds which have been established in Paraguay. Fitting of growth data in each breed to an empirical growth model with non-linear least square analysis resulted in the following age(t; months) - weight(w; kg) function made out each breed: w=638.26($1-2.341e^{-0.010965t}$) for Brahman and w=716.38($1-2.365e^{-0.10741t}$) for Santa Gertrudis. The estimated mature size of Brahman steers(638 kg) was 11% lower than that of Santa Gertrudis steers(716 kg). However, slightly larger k value (rate of maturing) of Brahman steer in the mechanistic model suggested relatively earlier maturing tendency in the breed. No significant differences in dressing percentage (Brahman, 59.3%; Santa Gertrudis, 58.8%) of chilled carcass weight to live-weight were observed between breed.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.4
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• pp.554-561
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• 2013

In this paper, we introduce a modeling and a process simulator developed with the aid of pRBFNNs for activated sludge process in the sewage treatment system. Activated sludge process(ASP) of sewage treatment system facilities is a process that handles biological treatment reaction and is a very complex system with non-linear characteristics. In this paper, we carry out modeling by using essential ASP factors such as water effluent quality, the manipulated value of various pumps, and water inflow quality, and so on. Intelligent algorithms used for constructing process simulator are developed by considering multi-output polynomial radial basis function Neural Networks(pRBFNNs) as well as Fuzzy C-Means clustering and Particle Swarm Optimization. Here, the apexes of the antecedent gaussian functions of fuzzy rules are decided by C-means clustering algorithm and the apexes of the consequent part of fuzzy rules are learned by using back-propagation based on gradient decent method. Also, the parameters related to the fuzzy model are optimized by means of particle swarm optimization. The coefficients of the consequent polynomial of fuzzy rules and performance index are considered by the Least Square Estimation and Mean Squared Error. The descriptions of developed process simulator architecture and ensuing operation method are handled.

• Smart Structures and Systems
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• v.6 no.9
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• pp.1057-1077
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• 2010

An early detection of structural damages is critical for the decision making of repair and replacement maintenance in order to guarantee a specified structural reliability. Consequently, the structural damage detection, based on vibration data measured from the structural health monitoring (SHM) system, has received considerable attention recently. The traditional time-domain analysis techniques, such as the least square estimation (LSE) method and the extended Kalman filter (EKF) approach, require that all the external excitations (inputs) be available, which may not be the case for some SHM systems. Recently, these two approaches have been extended to cover the general case where some of the external excitations (inputs) are not measured, referred to as the adaptive LSE with unknown inputs (ALSE-UI) and the adaptive EKF with unknown inputs (AEKF-UI). Also, new analysis methods, referred to as the adaptive sequential non-linear least-square estimation with unknown inputs and unknown outputs (ASNLSE-UI-UO) and the adaptive quadratic sum-squares error with unknown inputs (AQSSE-UI), have been proposed for the damage tracking of structures when some of the acceleration responses are not measured and the external excitations are not available. In this paper, these newly proposed analysis methods will be compared in terms of accuracy, convergence and efficiency, for damage identification of structures based on experimental data obtained through a series of laboratory tests using a scaled 3-story building model with white noise excitations. The capability of the ALSE-UI, AEKF-UI, ASNLSE-UI-UO and AQSSE-UI approaches in tracking the structural damages will be demonstrated and compared.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.2
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• pp.204-210
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• 2005

This paper presents online identification algorithm for TSK fuzzy model. The proposed algorithm identify structure of premise part by using distance, and obtain the parameters of the piecewise linear function consisting consequent part by using recursive least square. Only input space was considered in Most researches on structure identification, but input and output space is considered in the proposed algorithm. By doing so, outliers are excluded in clustering effectively. The existing other algorithm has disadvantage that it is sensitive to noise by using data itself as cluster centers. The proposed algorithm is non-sensitive to noise not by using data itself as cluster centers. Model can be obtained through one pass and it is not needed to memorize many data in the proposed algorithm.

• Journal of Ocean Engineering and Technology
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• v.36 no.3
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• pp.143-152
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• 2022

To reach a port, a ship must pass through a shallow water zone where seabed effects alter the hydrodynamics acting on the ship. This study examined the maneuvering characteristics of an autonomous surface ship at 3-DOF (Degree of freedom) motion in deep water and shallow water based on the in-port speed of 1.54 m/s. The CFD (Computational fluid dynamics) method was used as a specialized tool in naval hydrodynamics based on the RANS (Reynolds-averaged Navier-Stoke) solver for maneuvering prediction. A virtual captive model test in CFD with various constrained motions, such as static drift, circular motion, and combined circular motion with drift, was performed to determine the hydrodynamic forces and moments of the ship. In addition, a model test was performed in a square tank for a static drift test in deep water to verify the accuracy of the CFD method by comparing the hydrodynamic forces and moments. The results showed changes in hydrodynamic forces and moments in deep and shallow water, with the latter increasing dramatically in very shallow water. The velocity fields demonstrated an increasing change in velocity as water became shallower. The least-squares method was applied to obtain the hydrodynamic coefficients by distinguishing a linear and non-linear model of the hydrodynamic force models. The course stability, maneuverability, and collision avoidance ability were evaluated from the estimated hydrodynamic coefficients. The hydrodynamic characteristics showed that the course stability improved in extremely shallow water. The maneuverability was satisfied with IMO (2002) except for extremely shallow water, and collision avoidance ability was a good performance in deep and shallow water.

• Journal of Biosystems Engineering
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• v.41 no.3
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• pp.273-280
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• 2016

Purpose: This experiment was conducted to detect water stress in terms of the moisture content of cucumber seedlings under water stress condition using a hyperspectral image acquisition system, linear regression analysis, and partial least square regression (PLSR) to achieve a non-destructive measurement procedure. Methods: Changes in the reflectance spectrum of cucumber seedlings under water stress were measured using hyperspectral imaging techniques. A model for estimating moisture content of cucumber seedlings was constructed through a linear regression analysis that used the moisture content of cucumber seedlings and a normalized difference vegetation index (NDVI). A model using PLSR that used the moisture content of cucumber seedlings and reflectance spectrum was also created. Results: In the early stages of water stress, cucumber seedlings recovered completely when sub-irrigation was applied. However, the seedlings suffering from initial wilting did not recover when more than 42 h passed without irrigation. The reflectance spectrum of seedlings under water stress decreased gradually, but increased when irrigation was provided, except for the seedlings that had permanently wilted. From the results of the linear regression analysis using the NDVI, the model excluding wilted seedlings with less than 20% (n=97) moisture content showed a precision ($R^2$ and $R^2_{\alpha}$) of 0.573 and 0.568, respectively, and accuracy (RE) of 4.138% and 4.138%, which was higher than that for models including all seedlings (n=100). For PLS regression analysis using the reflectance spectrum, both models were found to have strong precision ($R^2$) with a rating of 0.822, but accuracy (RMSE and RE) was higher in the model excluding wilted seedlings as 5.544% and 13.65% respectively. Conclusions: The estimation model of the moisture content of cucumber seedlings showed better results in the PLSR analysis using reflectance spectrum than the linear regression analysis using NDVI.

• 한국전기화학회:학술대회논문집
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• 2001.11a
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• pp.145-161
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• 2001

Novel characterization of thermal properties of a battery has been introduced by defining its frequency-dependent thermal impedance function. Thermal impedance function can be approximated as a thermal impedance spectrum by analyzing experimental temperature transient which is related to the thermal impedance function through Laplace transformation. In order to obtain temperature transient, a process has been devised to generate external heat pulse with heating wire and to measure the response of battery. This process is used to study several commercial Li-ion batteries of cylindrical type. The thermal impedance measurements have been performed using potentionstat/galvanostate controlled digital signal processor, which is more commonly available than flow-meter usually applied for thermal property measurements. Thermal impedance spectra obtained for batteries produced by different manufactures are found to differ considerably. Comparison of spectra at different states of charge indicates independence of thermal impedance on charging state of battery. It is shown that thermal impedance spectrum can be used to obtain simultaneously thermal capacity and thermal conductivity of battery by non-linear complex least-square fit of the spectrum to thermal impedance model. Obtained data is used to simulate a response of the battery to internal heating during discharge. It is found that temperature inside the battery is by one-third larger that on its surface. This observation has to be considered to prevent damage by overheating.

• Journal of Navigation and Port Research
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• v.33 no.5
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• pp.323-330
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• 2009

We have been developing an underwater robot for harbour construction using a parallel mechanism The robot is attached to the rope of a crane, which curries a large stone into the undersea The robot's yaw and pitch are controlled by hydraulic cylinders but its roll is uncontrollable. We mount propellers in both side of the robot to generate the roll motion This paper studies on the control for the roll motion of a underwater robot. A gyro-sensor is used to measure the angle in a roll motion We develop the dynamic model to describe the robot's roll motion by a second order non-linear system and identify the model parameters by recursive least square and adaptive identifier. PD control, recursive model based control and adaptive model based control are applied with the dynamic model which computes the control input to compensate disturbances. This paper introduces the underwater robot system and presents the simulated and experimental results of the proposed controller.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.4112-4112
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• 2001

The feasibility of NIR spectroscopy as a quick and nondestructive method for quality control of uniformity of coating thickness of pharmaceutical tablets was investigated. Near infrared spectra of a set of pharmaceutical tablets with varying coating thickness were measured with a diffuse reflectance fiber optic probe connected to a Broker IFS 28/N FT-NIR spectrometer. The challenging issues encountered in this study included: 1. The similarity of the formulation of the core and coating materials, 2. The lack of sufficient calibration samples and 3. The non-linear relationship between the NIR spectral intensity and coating: thickness. A peak at 7184 $cm^{-1}$ was identified that differed for the coating material and the core material when M spectra were collected at 2 $cm^{-1}$ resolution (0.4 nm at 7184 $cm^{-1}$). The study showed that the coating thickness can be analyzed by polynomial fitting of the peak area of the selected peak, while least squares calibration of the same data failed due to the lack of availability of sufficient calibration samples. Samples of coal powder and solid pieces of coal were analyzed by FT-NIR diffuse reflectance spectroscopy with the goal of predicting their ash content, percentage of volatile components, and energy content. The measurements were performed on a Broker Vector 22N spectrometer with a fiber optic probe. A partial least squares model was constructed for each of the parameters of interest for solid and powdered sample forms separately. Calibration models varied in size from 4 to 10 PLS ranks. Correlation coefficients for these models ranged from 86.6 to 95.0%, with root-mean-square errors of cross validation comparable to the corresponding reference measurement methods. The use of FT-NIR diffuse reflectance measurement techniques was found to be a significant improvement over existing measurement methodologies in terms of speed and ease of use, while maintaining the desired accuracy for all parameters and sample forms.(Figure Omitted).