• Journal of Internet of Things and Convergence
• /
• v.9 no.2
• /
• pp.71-76
• /
• 2023

In this paper, we propose a smoothed received signal strength indicator (RSSI)-based distance estimation using deep neural network (DNN) for accurate distance estimation in an environment where a single receiver is used. The proposed scheme performs a data preprocessing consisting of data splitting, missing value imputation, and smoothing steps to improve distance estimation accuracy, thereby deriving the smoothed RSSI values. The derived smoothed RSSI values are used as input data of the Multi-Input Single-Output (MISO) DNN model, and are finally returned as an estimated distance in the output layer through input layer and hidden layer. To verify the superiority of the proposed scheme, we compared the performance of the proposed scheme with that of the linear regression-based distance estimation scheme. As a result, the proposed scheme showed 29.09% higher distance estimation accuracy than the linear regression-based distance estimation scheme.

• Journal of the Korean Data and Information Science Society
• /
• v.20 no.1
• /
• pp.77-87
• /
• 2009

Bayesian methods have been focused in recent years for solving small area estimation problems. In this paper, the hierarchical Bayes procedure is implemented via MCMC techniques and compared with the results of One-way, GLM-Normal, and GLM-Gamma cases by analyzing real data of insurance benefit for customer segmentations. After analyzing insurance benefit real data for customer segmentations, we can conclude that the insurance benefit estimator through the small area estimation is more efficient than the estimators by other methods. In addition, we found that the small area estimation gave accurate estimation result for the small number domains.

• Proceedings of the KIEE Conference
• /
• 2008.07a
• /
• pp.2092-2093
• /
• 2008

Since Jan. 2004, the Ministry of Construction and Transportation has partly introduced estimation system of historical cost data in order to reflect result cost of construction market to cost estimation for public construction. And KEPCO started estimation system of historical cost data in the electrical construction works. Electrical construction cost index a matter of great importance. This paper was conducted to examine estimation methods of the items of the price index estimation system of historical cost data and suggest reasonable applications.

• Journal of the Society of Naval Architects of Korea
• /
• v.52 no.1
• /
• pp.1-7
• /
• 2015

The weight estimation of floating offshore structures such as FPSO, TLP, semi-Submersibles, Floating Offshore Wind Turbines etc. in the preliminary design, is one of direct measures of both construction cost and basic performance. Through both literature investigation and internet search, the weight data of floating offshore structures such as FPSO and TLP was collected. In this study, the weight estimation model with the genetic programming was suggested for FPSO. The weight estimation model using genetic programming was established by fixing the independent variables based on this data. In addition, the correlation analysis was performed to make up for the weak points of genetic programming; it is apt to induce over-fitting when the number of data is relatively smaller than that of independent variables. That is, by reducing the number of variables through the analysis of the correlation between the independent variables, the increasing effect in the number of weight data can be expected. The reliability of the developed weight estimation model was within 2% of error rate.

• Smart Structures and Systems
• /
• v.15 no.2
• /
• pp.489-503
• /
• 2015

Response estimation at unmeasured locations using the limited number of measurements is an attractive topic in the field of structural health monitoring (SHM). Because of increasing complexity and size of civil engineering structures, measuring all structural responses from the entire body is intractable for the SHM purpose; the response estimation can be an effective and practical alternative. This paper investigates a response estimation technique based on the Kalman state estimator to combine multi-sensor data under non-zero mean input excitations. The Kalman state estimator, constructed based on the finite element (FE) model of a structure, can efficiently fuse different types of data of acceleration, strain, and tilt responses, minimizing the intrinsic measurement noise. This study focuses on the effects of (a) FE model error and (b) combinations of multi-sensor data on the estimation accuracy in the case of non-zero mean input excitations. The FE model error is purposefully introduced for more realistic performance evaluation of the response estimation using the Kalman state estimator. In addition, four types of measurement combinations are explored in the response estimation: strain only, acceleration only, acceleration and strain, and acceleration and tilt. The performance of the response estimation approach is verified by numerical and experimental tests on a simply-supported beam, showing that it can successfully estimate strain responses at unmeasured locations with the highest performance in the combination of acceleration and tilt.

• Journal of the Korean Data and Information Science Society
• /
• v.16 no.3
• /
• pp.657-663
• /
• 2005

Under the minimum risk point estimation formulation of Robbins(1959), we consider the sequential point estimation problem for normal population $N({\theta},\;{\theta})$ with unknown parameter ${\theta}$. In the case of completely unknown ${\theta}$, Stein's(1945) two-stage procedure is known to enjoy the consistency property, but it is not even first-order efficient. In the case when ${\theta}>{\theta}_L\;where\;{\theta}_L(>0)$ is known, the revised two-stage procedure is shown to enjoy all the usual second-order properties.

• Journal of the Korean Data and Information Science Society
• /
• v.14 no.4
• /
• pp.1055-1065
• /
• 2003

We shall propose maximum likelihood, Bayesian and generalized maximum likelihood estimation for the reliability of the two-unit hot standby system with exponential lifetime distribution that switch is perfect. Each estimation will be compared numerically in terms of various mission times, parameter values and asymptotic relative efficiency through Monte Carlo simulation.

• 제어로봇시스템학회:학술대회논문집
• /
• 2001.10a
• /
• pp.141.4-141
• /
• 2001

In this paper the Local Weighted Regression LWR technique is applied to the estimation of aircrcraft parameters. The method consists In improving the Local Weighted Regression LWR technique by adding a data Retention-and-Deletion RD strategy. The improvement comes with reduced computational effort since the two techniques can share their main computational procedures. The purpose of the study was to establish if the proposed algorithm could provide fast and reliable real-time estimations, with accuracy comparable to other well-known off-line identification schemes. The algorithm was tested using specific parameter estimation maneuvers and flight data of the NASA F/A-18 HARV. The results were compared with both the estimation obtained from ...

• 제어로봇시스템학회:학술대회논문집
• /
• 1987.10b
• /
• pp.446-450
• /
• 1987

In this paper, overdetermined method is used for high resolution spectral estimation in case of short data record length. To reduce the computational effort and to obtain recursive form of estimation algorithm, we modify data matrix to have near-Toeplitz structure. Then, new recursive algorithm is derived in the form of fast Kalman algorithm. Two stage procedure is used for the estimation of ARMA parameters. First AR parameters are estimated by using overdetermined modified Yule-walker equation, and then MA parameters are implicitly estimated by estimating numerator spectral coefficients(NS).

• Journal of the Korean Data and Information Science Society
• /
• v.11 no.2
• /
• pp.181-188
• /
• 2000

The shape of an M-estimation function is generally determined in the sense of either/both maximizing efficiency of an M-estimator at the model or/and bounding the influence function of an M-estimator. We propose an empirical method of choosing a value of the bending constant in Huber's ${\psi}-function$, which is the most widely used M-estimation function when estimating the location parameter.