• Advances in Energy Research
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• v.8 no.2
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• pp.111-123
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• 2022

Solar Energy is the energy of solar radiation carried by them in the form of heat and light. It can be converted into electricity. Solar potential depends on the site's atmosphere; the solar energy distribution depends on many factors, e.g., turbidity, cloud types, pollution levels, solar altitude, etc. We estimated solar radiation with the help of the Ashrae clear-sky model for three locations in Pakistan, namely Pasni, Gwadar, and Jiwani. As these locations are close to each other as compared to the distance between the sun and earth, therefore a slight change of latitude and longitude does not make any difference in the calculation of direct beam solar radiation (BSR), diffuse solar radiation (DSR), and global solar radiation (GSR). A modified formula for declination angle is also developed and presented. We also created two different models for Ashrae constants. The values of these constants are compared with the standard Ashrae Model. A good agreement is observed when we used these constants to calculate BSR, DSR, GSR, the Root mean square error (RMSE), Mean Absolute error (MABE), Mean Absolute percent error (MAPE), and chisquare (χ²) values are in acceptance range, indicating the validity of the models.

• Journal of Ecology and Environment
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• v.37 no.4
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• pp.177-184
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• 2014

This study was conducted to develop allometric equations and to determine the stem density and biomass expansion factor (BEF) for the estimation of the aboveground and belowground biomass of Cryptomeria japonica in Jeju Island, Korea. A total of 18 trees were harvested from the 40-year-old C. japonica stands in Hannam experimental forest, Jeju Island. The mean biomass of the C. japonica was $50.4Mg\;ha^{-1}$ in stem wood, $23.1Mg\;ha^{-1}$ in root, $9.6Mg\;ha^{-1}$ in branch, $4.6Mg\;ha^{-1}$ in needle and $4.3Mg\;ha^{-1}$ in stem bark. The diameter at breast height (DBH) was selected as independent variable for the development of allometric equations. To evaluate the performance of these equations, coefficient of determination ($R^2$) and root mean square error (RMSE) were used and results of the evaluation showed that $R^2$ ranged from 71% (root biomass equation) to 96% (aboveground biomass equation) and the RMSE ranged from 0.10 (aboveground biomass equation) to 0.33 (root biomass equation). The mean stem density of C. japonica was $0.37g\;cm^{-3}$ and the mean aboveground BEF was $1.28g\;g^{-1}$. Furthermore, the ratio of the root biomass to aboveground biomass was 0.32.

• Journal of the Korean Data and Information Science Society
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• v.17 no.2
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• pp.421-436
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• 2006

Huang proposed a grey-based nearest neighbor approach to predict accurately missing attribute value in 2004. Our study proposes which way to decide the number of nearest neighbors using not only the deng's grey relational grade but also the wen's grey relational grade. Besides, our study uses not an arithmetic(unweighted) mean but a weighted one. Also, GRG is used by a weighted value when we impute missing values. There are four different methods - DU, DW, WU, WW. The performance of WW(Wen's GRG & weighted mean) method is the best of any other methods. It had been proven by Huang that his method was much better than mean imputation method and multiple imputation method. The performance of our study is far superior to that of Huang.

• 한국데이터정보과학회:학술대회논문집
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• 2006.04a
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• pp.55-62
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• 2006

Huang proposed a grey-based nearest neighbor approach to predict accurately missing attribute value in 2004. Our study proposes which way to decide the number of nearest neighbors using not only the dong's grey relational grade but also the wen's grey relational grade. Besides, our study uses not an arithmetic(unweighted) mean but a weighted one. Also, GRG is used by a weighted value when we impute a missing values. There are four different methods - DU, DW, WU, WW. The performance of WW(wen's GRG & weighted mean) method is the best of my other methods. It had been proven by Huang that his method was much better than mean imputation method and multiple imputation method. The performance of our study is far superior to that of Huang.

• Wind and Structures
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• v.26 no.2
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• pp.99-114
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• 2018

Due to shortage of land and architectural aesthetics, sometimes the buildings are constructed as unconventional in plan. The wind force acts differently according to the plan shape of the building. So, it is of utter importance to study wind force or, more specifically wind pressure on an unconventional plan shaped tall building. To address this issue, this paper demonstrates a comprehensive study on mean pressure coefficient of 'E' plan shaped tall building. This study has been carried out experimentally and numerically by wind tunnel test and computational fluid dynamics (CFD) simulation respectively. Mean wind pressures on all the faces of the building are predicted using wind tunnel test and CFD simulation varying wind incidence angles from $0^{\circ}$ to $180^{\circ}$ at an interval of $30^{\circ}$. The accuracy of the numerically predicted results are measured by comparing results predicted by CFD with experimental results and it seems to have a good agreement with wind tunnel results. Besides wind pressures, wind flow patterns are also obtained by CFD for all the wind incidence angles. These flow patterns predict the behavior of pressure variation on the different faces of the building. For better comparison of the results, pressure contours on all the faces are also predicted by both the methods. Finally, polynomial expressions as the sine and cosine function of wind angle are proposed for obtaining mean wind pressure coefficient on all the faces using Fourier series expansion. The accuracy of the fitted expansions are measured by sum square error, $R^2$ value and root mean square error.

• Journal of Korea Water Resources Association
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• v.39 no.8 s.169
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• pp.659-668
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• 2006

The uncertainty of the risk of failure of hydraulic structures can be determined by estimating the variance of the risk of failure based on the methods of moments, probability weighted moments, and maximum likelihood assuming that the underlying model is the Gumbel distribution. In this paper, the variance of the risk of failure was derived. Monte Carlo simulation was peformed to verify the characteristics of the derived formulas for various sample size, design life, nonexceedance probability, and variation coefficient. As the results, PWM showed the smallest relative bias and root mean square error than the others while ML showed the smallest ones for relatively large sample siBes regardless of design life and nonexceedance probability. Also, it was found that variation coefficient does not effect on the relative bias and relative root mean square error.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.45 no.6
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• pp.108-116
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• 2008

In this paper, we propose an algorithm that can estimate the distance using disparity based on stereo vision system, even though the obstacle is located in long ranges as well as short ranges. We use sub-pixel interpolation to minimize quantization errors which deteriorate the distance accuracy when calculating the distance with integer disparity, and also we use enhanced adaptive fuzzy strong tracking Kalman filter(EAFSTKF) to improve the distance accuracy and track the path optimally. The proposed method can solve the divergence problem caused by nonlinear dynamics such as various vehicle movements in the conventional Kalman filter(CKF), and also enhance the distance accuracy and reliability. Our simulation results show that the performance of our method improves by about 13.5% compared to other methods in point of root mean square error rate(RMSER).

• Journal of Navigation and Port Research
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• v.32 no.8
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• pp.611-619
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• 2008

The Ministry of Land, Transport and Maritime Affairs is working on the construction of Nationwide DGPS(NDGPS) with connection to Maritime DGPS Reference Stations and if Chun-cheon Reference Station is to be completed in 2008, DGPS positioning information is available in the whole area of Republic of Korea. Therefore to promote the usage of DGPS surveying information, we measured and panalyzed the accuracy of DGPS. In real-time DGPS positioning accuracy were 0.42m of planar Root Mean Square(RMS) error in static survey and 0.48m of planar RMS error in dynamic survey. We went abreast with RTK comparison measurement. According to these results. DGPS positioning information cannot be applied directly to the GIS construction field, but GIS application fields, requiring the real-time positioning information. can take advantage of it in variable cases.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.8
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• pp.393-400
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• 2016

Recently, there have been various researches on efficient and automatic analysis on urban environment methods that utilize the computer vision and machine learning technology. Among many new analyses, urban safety analysis has received a major attention. In order to predict more accurately on safety score and reflect the human visual perception, it is necessary to consider the generic and local information that are most important to human perception. In this paper, we use Double-column Convolutional Neural network consisting of generic and local columns for the prediction of urban safety. The input of generic and local column used re-sized and random cropped images from original images, respectively. In addition, a new learning method is proposed to solve the problem of over-fitting in a particular column in the learning process. For the performance comparison of our Double-column Convolutional Neural Network, we compare two Support Vector Regression and three Convolutional Neural Network models using Root Mean Square Error and correlation analysis. Our experimental results demonstrate that our Double-column Convolutional Neural Network model show the best performance with Root Mean Square Error of 0.7432 and Pearson/Spearman correlation coefficient of 0.853/0.840.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.25 no.7
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• pp.782-790
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• 2014

In this paper, we apply the 2-D Matrix Pencil Method(MPM) to the estimation of the direction of arrival(DOA) of multiple signals of interest(SOIs) in bistatic MIMO radar. The 2-D MPM shows remarkable performance under a low SNR environment and low computational complexity to estimate the DOA of multiple SOIs. Also, it is possible to estimate the direction of departure(DOD) which is an angle from transmitter to target. To verify the proposed algorithm, we applied the proposed algorithm to a uniformly spaced linear array(ULA) and compared the RMSE(Root Mean Square Error) of DOA and DOD under the various SNR with those of the 2-D Capon algorithm.