• Journal of Biosystems Engineering
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• v.24 no.4
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• pp.301-308
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• 1999

Path planning for field operation of agricultural machinery is an indispensible part for precision farming or autonomous field operation. In this study, two algorithms (I, II) of generating a time-based shortest operation path were suggested to plan an optimal operation of an agricultural tractor-implement in a rectangular shaped field. The algorithms were based on modification of a minimum spanning tree algorithm, and applied for tractor-implement operations. the generated path was consisted of round operation and returning operation sections. The number of round operation was determined from the condition that a tractor can turn smoothly at headlands. The performance of the algorithms was evaluated by the calculation number for path generation and the total path length generated. Their stability was affected by the number of returning operation, but the algorithm II was considered to be more stable. In addition, the performances of the developed algorithms were compared with those of the conventional field operations at selected field sizes and shapes. The results showed that the algorithms could reduce field operation time greatly. For a 100m$\times$40m field, the reduced path length was 78m. The study also included an user interface program for implementing the algorithms and generating GPS coordinates that could be used in GIS softwares for precision farming.

• Journal of Positioning, Navigation, and Timing
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• v.10 no.3
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• pp.197-206
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• 2021

We compared two typical ensemble time scale algorithms; AT1 and Kalman filter. Four commercial atomic clocks composed of two hydrogen masers and two cesium atomic clocks provided measurement data to the algorithms. The allocation of relative weights to the clocks is important to generate a stable ensemble time. A 30 day-average-weight model, which was obtained from the average Allan variance of each clock, was applied to the AT1 algorithm. For the reduced Kalman filter (Kred) algorithm, we gave the same weights to the two hydrogen masers. We also compared the frequency stabilities of the outcome from the algorithms when the frequency offsets and/or the frequency drift offsets estimated by the algorithms were corrected or not corrected by the KRISS-made primary frequency standard, KRISS-F1. We found that the Kred algorithm is more effective to generate a stable ensemble time scale in the long-term, and the algorithm also generates much enhanced short-term stability when the frequency offset is used for the calculation of the Allan deviation instead of the phase offset.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.5
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• pp.1649-1665
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• 2021

In view of the low accuracy of the traditional FunkSVD algorithm, and in order to improve the computational efficiency of the algorithm, this paper proposes a parallel algorithm of improved FunkSVD based on Spark (SP-FD). Using RMSProp algorithm to improve the traditional FunkSVD algorithm. The improved FunkSVD algorithm can not only solve the problem of decreased accuracy caused by iterative oscillations but also alleviate the impact of data sparseness on the accuracy of the algorithm, thereby achieving the effect of improving the accuracy of the algorithm. And using the Spark big data computing framework to realize the parallelization of the improved algorithm, to use RDD for iterative calculation, and to store calculation data in the iterative process in distributed memory to speed up the iteration. The Cartesian product operation in the improved FunkSVD algorithm is divided into blocks to realize parallel calculation, thereby improving the calculation speed of the algorithm. Experiments on three standard data sets in terms of accuracy, execution time, and speedup show that the SP-FD algorithm not only improves the recommendation accuracy, shortens the calculation interval compared to the traditional FunkSVD and several other algorithms but also shows good parallel performance in a cluster environment with multiple nodes. The analysis of experimental results shows that the SP-FD algorithm improves the accuracy and parallel computing capability of the algorithm, which is better than the traditional FunkSVD algorithm.

• Nuclear Engineering and Technology
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• v.54 no.1
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• pp.310-317
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• 2022

The mass attenuation coefficient is the primary physical parameter to model narrow beam gamma-ray attenuation. A new machine learning based approach is proposed to model gamma-ray shielding behavior of composites alternative to theoretical calculations. Two fuzzy logic algorithms and a neural network algorithm were trained and tested with different mixture ratios of vanadium slag/epoxy resin/antimony in the 0.05 MeV-2 MeV energy range. Two of the algorithms showed excellent agreement with testing data after optimizing adjustable parameters, with root mean squared error (RMSE) values down to 0.0001. Those results are remarkable because mass attenuation coefficients are often presented with four significant figures. Different training data sizes were tried to determine the least number of data points required to train sufficient models. Data set size more than 1000 is seen to be required to model in above 0.05 MeV energy. Below this energy, more data points with finer energy resolution might be required. Neuro-fuzzy models were three times faster to train than neural network models, while neural network models depicted low RMSE. Fuzzy logic algorithms are overlooked in complex function approximation, yet grid partitioned fuzzy algorithms showed excellent calculation efficiency and good convergence in predicting mass attenuation coefficient.

• Proceedings of the KIEE Conference
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• 1999.07c
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• pp.1506-1509
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• 1999

This paper presents a new economic dispatch algorithm to improve the unit commitment solution while guaranteeing the near optimal solution without reducing calculation speed. The conventional economic dispatch algorithms have the problem that it is not applicable to the unit commitment formulation due to the frequent on/off state changes of units during the unit commitment calculation. Therefore, piecewise linear iterative method have generally been used for economic dispatch algorithm for unit commitment. In that method, the approximation of the generator cost function makes it hard to obtain the optimal economic dispatch solution. In this case, the solution can be improved by introducing a inverse of the incremental cost function. The proposed method is tested with sample system. The results are compared with the conventional piecewise linear iterative method. It is shown that the proposed algorithm yields more accurate and economical solution without calculation speed reduction.

• Proceedings of the KIEE Conference
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• 2015.07a
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• pp.416-417
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• 2015

In this study, the parameters of the lightning flashover rate calculation algorithm in South Korea, USA, Japan are investigated for the suitable algorithm for South Korea. Each parameters used in each calculation algorithms have a obvious difference by the environment of the area and transmission lines, because they have different environmental parameters respectively. In this paper, the environmental parameters are weighted according to the change of outputs by different inputs, environmental parameters. In addition, the methods of the selection CRIEPI algorithm and the application EPRI, CRIEPI parameters for improvement the KEPRI algorithm are proposed.

• Journal of the Korean Society of Safety
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• v.12 no.4
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• pp.180-190
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• 1997

A new method in the fault tree analysis (FTA) for the reliability calculation is suggested. Two steps are necessary in traditional method in evaluation of the occurrence probability of top event in fault tree (FT). The first step is to find the minimal outsets, and the second one is to substitute the result into the poincare equation. In order to reduce the enormous computing time of this method, lots of rapid algorithms have been developed. Almost of all achievements were, however, based on the partial structural properties of FT. In this paper, the FT is transformed to a non-linear graph G which has the same minimal outsets of original n, and then the reliability is calculated using the domination theory. In this new method, the required number of equation terms are at most $2^n$ (n is node number of graph G), while $2^m$-1 (m is the number of minimal cutsets) calculation terms are required in the poincare equation in traditional method. Since m>>n in general. our new method reduces the calculation time significantly.

• Nuclear Engineering and Technology
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• v.37 no.2
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• pp.167-176
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• 2005

We developed the PERUPS system to aid the on-line performance analysis for the turbine cycle of the YongGwang 3 and 4 nuclear power plants. Procedure of measurement validation is included in the performance calculation to obtain heat balance. Precision of on-line performance calculation is increased via practical modifications of standard calculation algorithms based on the PTC (Performance Test Code). The proposed system also provides useful Web-based aids for performance analysis, including performance data management, a graphic viewer for heat balance and turbine expansion lines, and synthesized reports of performance.

• Journal of the Korean Society for Precision Engineering
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• v.17 no.1
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• pp.52-60
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• 2000

In order to design a reliable machine component efficiently, it is necessary to set up the process of durability analysis using computer simulation technique. In this paper, two methods for dynamic stress calculation, which are basis of durability analysis, are reviewed. Then, a user-oriented dynamic stress analysis program is developed from these two algorithms together with a general-purpose flexible body dynamic analysis and structural analysis programs. Finally, a slider-crank mechanism which has a flexible connecting-rod is chosen to show the special characteristics of these two dynamic stress calculation methods.

• The Transactions of the Korean Institute of Power Electronics
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• v.23 no.6
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• pp.381-388
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• 2018

A novel and simple algorithm for accurate calculation of RMS voltage is proposed in a digitally controlled grid-tie inverter system. Given that the actual frequency of grid voltage is continuously changing, the constant sampling frequency cannot be a multiple number of the fundamental frequency. Therefore, the RMS of grid voltage contains periodic oscillations due to the differences in the phase angle of sampled data during calculation. The proposed algorithm precisely calculates and updates the initial phase angle of the first sampled voltage in a half-cycle period using phase-locked loop, which is commonly utilized for phase angle detection in grid-tie inverter systems. The accuracy and dynamic performance of the proposed algorithm are compared with those of other algorithms through various simulations and experiments.