• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.23 no.10
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• pp.36-44
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• 2009

This paper analyzes efficiency of photovoltaic(PV) tracking system using position solar algorithm(PSA). Solar location tracking system is needed for efficiently and intensively using PV system independent of environmental condition. PV tracking system of program method is presented a high tracking accuracy without the wrong operating in rapidly changing insolation by the clouds and atmospheric condition. Therefore, this paper analyzes efficiency of PV system using PSA algorithm for more correct position tracking of solar. Also, controlled altitude angle and azimuth angle by applied algorithm is compared with data of korea astronomy observatory. And this paper analyzes the tracking error and generation efficiency then proves the validity of applied algorithm.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2009.05a
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• pp.412-415
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• 2009

This paper analyzes efficiency of photovoltaic(PV) tracking system using position solar algorithm(PSA). Solar location tracking system is needed for efficiently and intensively using PV system independent of environmental condition. PV tracking system of program method is presented a high tracking accuracy without the wrong operating in rapidly changed insolation by the clouds and atmospheric condition. Therefore, this paper analyzes efficiency of PV system using PSA algorithm for more correct position tracking of solar. Also, controlled altitude angle and azimuth angle by applied algorithm is compared with data of korea astronomy observatory. And this paper analyzes the tracking error and roves the validity of applied algorithm.

• Journal of Information Processing Systems
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• v.16 no.2
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• pp.478-493
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• 2020

We designed a new meta-heuristic algorithm named Photon Search Algorithm (PSA) in this paper, which is motivated by photon properties in the field of physics. The physical knowledge involved in this paper includes three main concepts: Principle of Constancy of Light Velocity, Uncertainty Principle and Pauli Exclusion Principle. Based on these physical knowledges, we developed mathematical formulations and models of the proposed algorithm. Moreover, in order to confirm the convergence capability of the algorithm proposed, we compared it with 7 unimodal benchmark functions and 23 multimodal benchmark functions. Experimental results indicate that PSA has better global convergence and higher searching efficiency. Although the performance of the algorithm in solving the optimal solution of certain functions is slightly inferior to that of the existing heuristic algorithm, it is better than the existing algorithm in solving most functions. On balance, PSA has relatively better convergence performance than the existing metaheuristic algorithms.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.1115-1116
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• 2011

This paper proposes tracking solar power generation system using position solar algorithm(PSA). The solar power generation is changed power according to solar position due to using solar energy. The solar tracking methods are the program method and sensor method. This paper proposes two-axis tracking solar power generation using program tracking method. The validity of proposed system in this paper is proved through analyzing temperature of solar collect, generating power and efficiency.

• Journal of the Korean Institute of Telematics and Electronics
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• v.18 no.6
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• pp.9-15
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• 1981

A new algorithm is presented from minimiEing the gates cost and gate inputs cost for the multiple-output TANT networks. In this algorithm, multiple-output map is organized and multiple-output function is constructed by using combination of minterms in order of the number of head variables. Systematic combination is made by PSA algorithm, and so the total design procedure is simplified.

• Korean Journal of Optics and Photonics
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• v.33 no.1
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• pp.11-21
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• 2022

We have investigated the optimal design of an aperiodic optical phased array (OPA) for use in light detection and ranging applications. Three optimization algorithms - particle-swarm optimization (PSO), a genetic algorithm (GA), and a pattern-search algorithm (PSA) - were employed to obtain the optimal arrangement of optical antennas comprising an OPA. The optimization was performed to obtain the minimal side-lobe level (SLL) of an aperiodic OPA at each steering angle, using the three optimization algorithms. It was found that PSO and GA exhibited similar results for the SLL of the optimized OPA, while the SLL obtained by PSA showed somewhat different features from those obtained by PSO and GA. For an OPA optimized at a steering angle <45°, the SLL value averaged over all steering angles increased as the angle of optimization decreased. However, when the angle of optimization was larger than 45°, low average SLL values of <13 dB were obtained for all three optimization algorithms. This implies that an OPA with high signal quality can be obtained when the arrangement of the optical antennas is optimized at a large steering angle.

• Coupled systems mechanics
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• v.13 no.1
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• pp.1-19
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• 2024

The effectiveness of coupling with a bolted rim is assessed in this research using a newly designed optimization algorithm. The current study, which is provided here, evaluates 10 contemporary metaheuristic approaches for enhancing the coupling with bolted rim design problem. The algorithms used are particle swarm optimization (PSO), crow search algorithm (CSA), enhanced honeybee mating optimization (EHBMO), Harmony search algorithm (HSA), Krill heard algorithm (KHA), Pattern search algorithm (PSA), Charged system search algorithm (CSSA), Salp swarm algorithm (SSA), Big bang big crunch optimization (B-BBBCO), Gradient based Algorithm (GBA). The contribution of the paper isto optimize the coupling with bolted rim problem by comparing these 10 algorithms and to find which algorithm gives the best optimized result. These algorithm's performance is evaluated statistically and subjectively.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.2
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• pp.520-541
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• 2023

In CRNs, SS is of utmost significance. Every CR user generates a sensing report during the training phase beneath various circumstances, and depending on a collective process, either communicates or remains silent. In the training stage, the fusion centre combines the local judgments made by CR users by a majority vote, and then returns a final conclusion to every CR user. Enough data regarding the environment, including the activity of PU and every CR's response to that activity, is acquired and sensing classes are created during the training stage. Every CR user compares their most recent sensing report to the previous sensing classes during the classification stage, and distance vectors are generated. The posterior probability of every sensing class is derived on the basis of quantitative data, and the sensing report is then classified as either signifying the presence or absence of PU. The ISVM technique is utilized to compute the quantitative variables necessary to compute the posterior probability. Here, the iterations of SVM are tuned by novel GO-PSA by combining GOA and PSO. Novel GO-PSA is developed since it overcomes the problem of computational complexity, returns minimum error, and also saves time when compared with various state-of-the-art algorithms. The dependability of every CR user is taken into consideration as these local choices are then integrated at the fusion centre utilizing an innovative decision combination technique. Depending on the collective choice, the CR users will then communicate or remain silent.

• Journal of the Korean Society of Safety
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• v.30 no.3
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• pp.100-106
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• 2015

A module or independent subtree is a part of a fault tree whose child gates or basic events are not repeated in the remaining part of the fault tree. Modules are necessarily employed in order to reduce the computational costs of fault tree quantification. This quantification generates fault tree solutions such as minimal cut sets, minimal path sets, or binary decision diagrams (BDDs), and then, calculates top event probability and importance measures. This paper presents a new linear time algorithm to detect modules of large fault trees. It is shown through benchmark tests that the new method proposed in this study can very quickly detect the modules of a huge fault tree. It is recommended that this method be implemented into fault tree solvers for efficient probabilistic safety assessment (PSA) of nuclear power plants.

• Journal of Korean Society for Quality Management
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• v.39 no.2
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• pp.320-328
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• 2011

This research proposes comprehensive models for analyzing common cause failures (CCF) due to cumulative shocks and to assess system reliability under the CCF. The proposed cumulative shock models are based on the binomial failure rate (BFR) model. Six kinds of models are proposed so as to explain diverse cumulative shock phenomena. The models are composed of the initial failure probability, shape parameter, and the total shock number. Some parameters of the proposed models can not be explicitly estimated, so we adopt the Expectation-maximization (EM) algorithm in order to obtain the maximum likelihood estimator (MLE) for the parameters. By estimating the parameters for the cumulative shock models, the system reliability with CCF can be assessed sequentially according to the number of cumulative shocks. The result can be utilizes in dynamic probabilistic safety assessment (PSA), aging studies, or risk management for nuclear power plants. Replacement or maintenance policies can also be developed based on the proposed model.