• Geomechanics and Engineering
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• v.15 no.1
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• pp.631-643
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• 2018

The estimation of the strength and other mechanical parameters characterizing the tensile behavior of granites can play an important role in civil engineering tasks such as design, construction, rehabilitation and repair of existing structures. The purpose of this paper is to apply data mining techniques, such as multiple regression (MR), artificial neural networks (ANN) and support vector machines (SVM) to estimate the mechanical properties of granites. In a first phase, the mechanical parameters defining the complete tensile behavior are estimated based on the tensile strength. In a second phase, the estimation of the mechanical properties is carried out from different combination of the physical properties (ultrasonic pulse velocity, porosity and density). It was observed that the estimation of the mechanical properties can be optimized by combining different physical properties. Besides, it was seen that artificial neural networks and support vector machines performed better than multiple regression model.

• The Journal of the Acoustical Society of Korea
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• v.18 no.1E
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• pp.3-6
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• 1999

In digital mobile communication system, the transmission errors affect the quality of output speech seriously. There are many error concealment techniques using a posteriori probability which provides information about any transmitted parameter. They need knowledge about channel transition probability as well as the 1st order Markov transition probability of codec parameters for estimation of transmitted parameters. However, in applications of mobile communication systems, the channel transition probability varies depending on nonstationary channel characteristics. The mismatch of designed channel transition probability of the estimator to actual channel transition probability degrades the performance of the estimator. In this paper, we proposed a new parameter estimator which adapts to the channel characteristics using short time average of maximum a posteriori probabilities(MAPs). The proposed scheme, when applied to the LSP parameter estimation, performed better than the conventional estimator which do not adapt to the channel characteristics.

• Journal of Drive and Control
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• v.9 no.2
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• pp.15-20
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• 2012

Pneumatic cylinder meter-out driving apparatus is used widely because it is clean, lightweight, and can be easily serviced. In this study an estimation method of energy consumption for pneumatic cylinder meter-out driving apparatus is proposed. The proposed method is derived from state equation and energy equation of air, and, the equation of motion of a moving part of a pneumatic cylinder reflecting the characteristics of the meter-out driving. The effectiveness of the proposed method is proved by simulation study and it demonstrates that the proposed method can evaluate the energy consumption quickly and easily when the parameters of the driving apparatus are changed.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2002.05a
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• pp.298-302
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• 2002

Equivalent volume estimation of the coupler and two coupled microphones has a key role in standard microphone pressure calibration. The equivalent volume of the microphone is determined by the dynamic characteristics of the diaphragm system and front cavity. Therefore the modal parameters of diaphragm system - natural frequency and damping fatter - should be measured explicitly for the estimation of the equivalent volume. The diaphragm system is composed of the vibrating diaphragm, back slit behind diaphragm, pressure equalization vent, and front cavity which are acoustically coupled. In the measurement, the electrostatic actuator was used to excite the system with the swept sine, and the frequency response was obtained. The close actuator in front of the diaphragm must influence the radiation impedance of the system, and then the modal parameters. From the measured frequency response, the natural frequency and the damping factor could be estimated with the Complex exponential method based on the Prony model and the zero crossing real and imaginary plot.

• Industrial Engineering and Management Systems
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• v.1 no.1
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• pp.79-86
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• 2002

This paper proposes a new algorithm for estimating ARMA model parameters. In estimating ARMA model parameters, several methods such as generalized least square method, instrumental variable method have been developed. Among these methods, the utilization of a bootstrap type algorithm is known as one of the effective approach for the estimation, but there are cases that it does not converge. Hence, in this paper, making use of a cross correlation function and utilizing the relation of structural a priori knowledge, a new bootstrap algorithm is developed. By introducing theoretical relations, it became possible to remove terms, which is liable to include much noise. Therefore, this leads to robust parameter estimation. It is shown by numerical examples that using this algorithm, all simulation cases converge while only half cases succeeded with the previous one. As for the calculation time, judging from the fact that we got converged solutions, our proposed method is said to be superior as a whole.

• Journal of Electrical Engineering and Technology
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• v.12 no.3
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• pp.1166-1176
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• 2017

Estimation errors of the rotor speed and position in sensorless control systems of Permanent Magnet Synchronous Motors (PMSM) will lead to low efficiency and dynamic-performance degradation. In this paper, a parallel-type extended nonlinear observer incorporating the nominal parameters is constructed in the stator-fixed reference frame, with rotor position, speed, and the load torque simultaneously estimated. The stability of the extended nonlinear observer is analyzed using the indirect Lyapunov's method, and observer gains are selected according to the transfer functions of the speed and position estimators. Taking into account the parameter inaccuracies issue, explicit estimation error equations are derived based on the error dynamics of the closed-loop sensorless control system. An equivalent flux error is defined to represent the back Electromotive Force (EMF) error caused by the inaccurate motor parameters, and a compensation strategy is designed to suppress the estimation errors. The effectiveness of the proposed method has been validated through simulation and experimental results.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 1999.11a
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• pp.475-481
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• 1999

This paper presents a recursive least square estimation algorithm to estimate parameters of the vector controlled induction machine based on measurements of the stator voltage, curents and slip frequency. Due to its recursive structure, this algorithm has the potential to be used for on-line estimation and adaptive control. The algorithm is designed using regression model derived from the motor electrical equation. This model is valid when there is a tittle-scale separation between vector control system and adaptive system. Vector control performed at fast stage and slow stage is in charge of parameters estimation. The performance of tile algorithm is illustrated by means of simulation results and experiment.

• Journal of Electrical Engineering and Technology
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• v.13 no.3
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• pp.1363-1370
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• 2018

In visible light (VL) positioning based on angle of arrival (AOA) estimation for smart indoor service, the AOA parameters obtained at the receiver has sometimes a random and distributed angle form instead of a point angle form due to the multipath transfer of the actual visible light and short positioning distance. The AOA estimation of a VL signal with a random and parametric distributed angle form may give incorrect AOA parameter estimates, which may result in poor VL positioning performance. In this paper, we classify the AOA parameters of the received VL signal into three forms according to the actual positioning channel environment and consider the short-range VL positioning method. We propose a subspace-based AOA parameter estimation technique and a data fusion method, and analyzed the proposed method by simulation and the measurement of the real VL channel characteristics.

• The KIPS Transactions:PartD
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• v.16D no.5
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• pp.729-736
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• 2009

The accurate estimation of software development cost is important to a successful development in software engineering. Until recent days, the model using regression analysis based on statistical algorithm and machine learning method have been used. However, this paper estimates the software cost using support vector regression, a sort of machine learning technique. Also, it finds the best set of optimized parameters applying genetic algorithm. The proposed GA-SVR model outperform some recent results reported in the literature.

• Journal of Welding and Joining
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• v.29 no.6
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• pp.82-87
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• 2011

In this study, we conducted laser welding by using remote scanner that is 5J32 aluminum alloy to observe the mechanical properties and optimize welding process parameters. As the control factors, laser incident angle, laser power and welding speed were set and as the result of weldablility, tensile shear tests were performed. ANOVA (Analysis of Variation) was also carried out to identify the influence of process variables on tensile shear strength. Strength estimation models were suggested using regression alnalysis and 2nd order polynomial model had the best estimation performance. In addition optimal welding condition was determined in terms with wedalility and productivity using objective function and fitness function. Final optimized welding condition was laser power was 4 kW, and welding speed was 4.6 m/min.