• Communications for Statistical Applications and Methods
• /
• v.17 no.3
• /
• pp.357-365
• /
• 2010

This paper considers the integrated process control procedure for detecting special causes in an IMA(1,1) noise process that is being adjusted using a minimum mean squared error adjustment. As a SPC procedure, we use a GLR chart for detecting special causes whose effects are the sustained shift or the sustained drift in the process mean, and the sustained shift in the process variance. For the design of the GLR chart, we derive expressions for the control limit which accurately satisfies the given in-control ARL.

• Journal of the Korean Solar Energy Society
• /
• v.33 no.3
• /
• pp.17-26
• /
• 2013

The aim of this study is to analyze the performance of a parabolic trough solar collector (PTC) for water heating and to validate the model performance. The simulated model was compared, calibrated and verified with the experimental results. RMSE (Root mean square error) was used to calibrate the convective heat transfer coefficient between the absorber pipe and the ambient air which was the main factor affecting the heat transfer associated with the PTC. The calibrated model was better fitted with the experimental model. The maximum, minimum and mean deviation between the measured and predicted water temperatures differed only $0.81^{\circ}C$, $0.09^{\circ}C$ and $0.31^{\circ}C$ respectively in the calibrated model. RMSE values were decreased from 0.5389 to 0.4910, 0.0134 to 0.0125 and R-squared was increased from 0.9955 to 0.9956 after calibration. The temperature of water was increased from $33.7^{\circ}C$ to $48^{\circ}C$ in 12hour test. The thermal efficiency of the collector was calculated to be 55%. The calibrated model showed good agreement with the experimental data for model validation.

• Atmosphere
• /
• v.34 no.1
• /
• pp.23-34
• /
• 2024

The Korea Meteorological Administration has improved medium-range weather forecasts by implementing post-processing methods to minimize numerical model errors. In this study, we employ a statistical correction technique known as the minimum continuous ranked probability score (CRPS) to refine medium-range forecast guidance. This technique quantifies the similarity between the predicted values and the observed cumulative distribution function of the Unified Model Ensemble Prediction System for Global (UM EPSG). We evaluated the performance of the medium-range forecast guidance for surface air temperature and relative humidity, noting significant enhancements in seasonal bias and root mean squared error compared to observations. Notably, compared to the existing the medium-range forecast guidance, temperature forecasts exhibit 17.5% improvement in summer and 21.5% improvement in winter. Humidity forecasts also show 12% improvement in summer and 23% improvement in winter. The results indicate that utilizing the minimum CRPS for medium-range forecast guidance provide more reliable and improved performance than UM EPSG.

• Journal of IKEEE
• /
• v.16 no.2
• /
• pp.138-144
• /
• 2012

In this paper, a semi-analytical approach is proposed for DSF(Decode and Selective Forward)-Relay MC-CDMA(MultiCarrier-Code Division Multiple Access) systems over multipath Rayleigh fading channels. Considering BER(bit error rate) performance and complexity, the MMSE-C(Minimum Mean squared Error-per subCarrier) is used as the combining method for MC-CDMA systems. At first, the analytical method based on error-events at relay nodes for DSF-Relay schemes is utilized in order to derive the averaged BER. Then, the averaged BER is expressed as the form considering possible all error-events. Also, proposed semi-analytical expressions have been verified by comparing with simulation results. Finally, it is verified that the derived analytical expressions can be a frame work to cover different multipath Rayleigh fading channel conditions and to measure the upper performance for DSF-Relay MC-CDMA systems.

• Steel and Composite Structures
• /
• v.27 no.4
• /
• pp.427-438
• /
• 2018

In this paper, the single and multi-objective optimization of thin-walled conical tubes with different types of indentations under axial impact has been investigated using surrogate models called metamodels. The geometry of tapered thin-walled tubes has been studied in order to achieve maximum specific energy absorption (SEA) and minimum peak crushing force (PCF). The height, radius, thickness, tapered angle of the tube, and the radius of indentation have been considered as design variables. Based on the design of experiments (DOE) method, the generated sample points are computed using the explicit finite element code. Different surrogate models including Kriging, Feed Forward Neural Network (FNN), Radial Basis Neural Network (RNN), and Response Surface Modelling (RSM) comprised to evaluate the appropriation of such models. The comparison study between surrogate models and the exploration of indentation shapes have been provided. The obtained results show that the RNN method has the minimum mean squared error (MSE) in training points compared to the other methods. Meanwhile, optimization based on surrogate models with lower values of MSE does not provide optimum results. The RNN method demonstrates a lower crashworthiness performance (with a lower value of 125.7% for SEA and a higher value of 56.8% for PCF) in comparison to RSM with an error order of $10^{-3}$. The SEA values can be increased by 17.6% and PCF values can be decreased by 24.63% by different types of indentation. In a specific geometry, higher SEA and lower PCF require triangular and circular shapes of indentation, respectively.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.18 no.8
• /
• pp.1226-1237
• /
• 1993

For data transmission over strictly band-limited non-ideal channels, different types of filters with arbitrary responses are needed. In this paper. we proposed two efficient techniques for the design of such FIR filters whose response is specified in either the time or the frequency domain. In particular when a fractionally-spaced structure is used for the transceiver, these filters can be efficiently designed by making use of characteristics of oversampling. By using a minimum mean-squared error criterion, we design a fractionally-spaced FIR filter whose frequency response can be controlled without affecting the output error. With proper specification of the shape of the additive noise signals, for example, the design results in a receiver filter that can perform compromise equalization as well as phase splitting filtering for QAM demodulation. The second method ad-dresses the design of an FIR filter whose desired response can be arbitrarily specified in the frequency domain. For optimum design, we use an iterative optimization technique based on a weighted least mean square algorithm. A new adaptation algorithm for updating the weighting function is proposed for fast and stable convergence. It is shown that these two independent methods can be efficiently combined together for more complex applications.

• Advances in environmental research
• /
• v.5 no.3
• /
• pp.153-167
• /
• 2016

We applied multilayer perceptron (MLP) and radial basis function (RBF) neural network in upstream and downstream water quality stations of the Karaj Reservoir in Iran. For both neural networks, inputs were pH, turbidity, temperature, chlorophyll-a, biochemical oxygen demand (BOD) and nitrate, and the output was dissolved oxygen (DO). We used an MLP neural network with two hidden layers, for upstream station 15 and 33 neurons in the first and second layers respectively, and for the downstream station, 16 and 21 neurons in the first and second hidden layer were used which had minimum amount of errors. For learning process 6-fold cross validation were applied to avoid over fitting. The best results acquired from RBF model, in which the mean bias error (MBE) and root mean squared error (RMSE) were 0.063 and 0.10 for the upstream station. The MBE and RSME were 0.0126 and 0.099 for the downstream station. The coefficient of determination ($R^2$) between the observed data and the predicted data for upstream and downstream stations in the MLP was 0.801 and 0.904, respectively, and in the RBF network were 0.962 and 0.97, respectively. The MLP neural network had acceptable results; however, the results of RBF network were more accurate. A sensitivity analysis for the MLP neural network indicated that temperature was the first parameter, pH the second and nitrate was the last factor affecting the prediction of DO concentrations. The results proved the workability and accuracy of the RBF model in the prediction of the DO.

• Journal of the Korea Society of Computer and Information
• /
• v.26 no.9
• /
• pp.65-72
• /
• 2021

We consider the joint optimization problem of transmit power level, MMSE receiver filter and access point(AP) selection for multi access points environment. In the previous work, transmit power and MMSE receiver filter were jointly optimized[1] and transmit power and best access point were optimized jointly[2]. For each case, the algorithm was proposed and its convergence which guarantees the minimum total transmit power was proved. In this paper, we further improve the algorithm by jointly optimizing three parameters. More specifically, 1) we propose the algorithm by considering transmit power, MMSE receiver filter and access point selection jointly. 2) we prove that the proposed algorithm guarantees convergence with minimum transmit power consumption. In the simulation results, it is shown that proposed algorithm outperforms two other algorithms, i.e., 1) algorithm with transmit power and MMSE receiver filter, and 2) algorithm with transmit power and best access point selection.

• ETRI Journal
• /
• v.29 no.2
• /
• pp.143-152
• /
• 2007

In this paper, we propose a time-varying modified minimum mean-squared error (MMSE) detector for the detection of higher data rate signals in a multirate asynchronous code-division multiple-access (CDMA) system which is signaled in a fast Rayleigh fading channel. The interference viewed by a higher data rate symbol will be periodic due to the presence of a lower data rate symbol which spans multiple higher data rate symbols. The detection is carried out on the basis of a modified MMSE criterion which incorporates differential detection and the ratio of channel coefficients in two consecutive observation intervals inherently compensating the fast variation of the channel due to fading. The numerical results obtained by the MMSE detector with time-varying detection show around 3 dB (M=2) and 6 dB (M=4) performance improvement at a BER of $10^{-3}$ in the AWGN channel, while introducing more computational complexity than the MMSE detector without time-varying detection. At a higher $E_b/N_0$, the proposed scheme can achieve a BER of approximately $10^{-3}$ in the presence of fast channel variation which is an improvement over other schemes.

• 제어로봇시스템학회:학술대회논문집
• /
• 2003.10a
• /
• pp.502-507
• /
• 2003

Toward the development of practical methods for observed data oriented bispectral estimation, an automatic means for determining the smoothing bandwidth of bispectral windows is proposed, that can also provide an associated optimum bispectral estimate of stationary non-Gaussian signals, systematically only from an observed time series datum of finite length. For the conventional non-parametric bispectral estimation, the MSE (mean squared error) of the normalized estimate is reviewed under a certain mixing condition and sufficient data length, mainly from the viewpoint of the inverse relation between its bias and variance with respect to the smoothing bandwidth. Based on the fundamental relation, a systematic method not only for determining the bandwidth, but also for obtaining the optimum bispectral estimate is presented by newly introducing a MSE evaluation index of the estimate only from an observed time series datum of finite length. The effectiveness and fundamental features of the proposed method are illustrated by the basic results of numerical experiments.