• Journal of Satellite, Information and Communications
• /
• v.10 no.3
• /
• pp.57-61
• /
• 2015

This paper describes the basic principles of 3D broadcast system and proposes new 3D broadcast technology that reduces the amount of data by applying CS(Compressed Sensing). Differences between Sampling theory and the CS technology concept was described. CS algorithm SS-CoSaMP(Single-Space Compressive Sampling Matched Pursuit) and AMP(Approximate Message Passing) was described. Image data compressed and restored by these algorithm was compared. Calculation time of the algorithm having a low complexity is determined.

• Journal of the Korea Computer Graphics Society
• /
• v.4 no.1
• /
• pp.31-40
• /
• 1998

Active Contour Model(ACM) is an efficient method for segmenting an object. The main shortcoming of ACM is that its result is very dependent on the shape and location of an initial contour. To overcome this shortcoming, a new segmentation algorithm is proposed in this paper. The proposed algorithm uses B-splines to describe the active contour and applies Simulated Annealing (SA) and Genetic Algorithm(GA) as energy minimization techniques. We tried to overcome the initialization problem of traditional ACM and compared the result of ACM using GA and that using SA with 2D synthetic binary images. CT and MR images.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2003.11a
• /
• pp.104-108
• /
• 2003

Finite element (FE) model updating is a procedure to minimize the differences between analytical and experimental results, which can be usually posed as an optimization problem. This paper aims to introduce a hybrid optimization algorithm (GA-SA), which consists of a Genetic algorithm (GA) stage and an Adaptive Simulated Annealing (ASA) stage, to FE model updating for a shrunk shaft. A good agreement of the first four natural frequencies has been achieved obtained from GASA based updated model (FEgasa) and experiment. In order to prove the validity of GA-SA, comparisons of natural frequencies obtained from the initial FE model (FEinit), GA based updated model (FEga) and ASA based updated model (FEasa) are carried out. Simultaneously, the FRF comparisons obtained from different FE models and experiment are also shown. It is concluded that the GA, ASA, GA-SA are powerful optimization techniques which can be successfully applied to FE model updating, the natural frequencies and FRF obtained from all the updated models show much better agreement with experiment than that obtained from FEinit model. However, FEgasa is proved to be the most reasonable FE model, and also FEasa model is better than FEga model.

• Journal of Satellite, Information and Communications
• /
• v.9 no.3
• /
• pp.59-63
• /
• 2014

This paper describes the basic principles of 3D broadcast system and proposes new 3D broadcast technology that reduces the amount of data by applying CS(Compressed Sensing). Differences between Sampling theory and the CS technology concept were described. Recently proposed CS algorithm AMP(Approximate Message Passing) and CoSaMP(Compressive Sampling Matched Pursuit) were described. This paper compared an accuracy between two algorithms and a calculation time that image data compressed and restored by these algorithms. As result determines a low complexity algorithm for 3D broadcast system.

• IE interfaces
• /
• v.10 no.2
• /
• pp.1-13
• /
• 1997

The problem of the formation of machine-part cells in FMS is a very important issue at the planning and operating stages of FMS. This problem is inherently a combinatorial optimization problem, proven to be NP-complete(or, NP-hard). Among the several kinds of approaches which have been applied to solve the combinatorial optimization problems, the Simulated Annealing(SA) algorithm, a technique of random search type with a flexibility in generating alternatives, is a powerful problem solving tool. In this paper, the SA algorithm is used to solve machine cell-part family formation problems. The primary purpose of the study is to find the near-optimal solution of machine cell-part family formation problem, whare the product volume and number of operations are prespecified, that can minimize the total material handling cost caused by exceptional elements and intercell moves as much as possible. The results show that the SA algorithm is able to find a near-optimal solution for practical problems of the machine cell-part family formation.

• Journal of Electrical Engineering and Technology
• /
• v.8 no.5
• /
• pp.1012-1020
• /
• 2013

In this work, Self-adaptive Differential Evolutionary (SaDE) algorithm is proposed to solve Optimal Location and Size of Capacitor (OLSC) problem in radial distribution networks. To obtain the SaDE algorithm, two improvements have been applied on control parameters of mutation and crossover operators. To expand the study, three load conditions have been considered, i.e., constant, varying and effective loads. Objective function is introduced for the load conditions. The annual cost is fitness of problem, in addition to this cost, CPU time, voltage profile, active power loss and total installed capacitor banks and their related costs have been used for comparisons. To confirm the ability of each improvements of SaDE, the improvements are studied both in separate and simultaneous conditions. To verify the effectiveness of the proposed algorithm, it is tested on IEEE 10-bus and 34-bus radial distribution networks and compared with other approaches.

• Smart Structures and Systems
• /
• v.13 no.3
• /
• pp.389-406
• /
• 2014

Optimal sensor placement techniques play a significant role in enhancing the quality of modal data during the vibration based health monitoring of civil structures, where many degrees of freedom are available despite a limited number of sensors. The literature has shown a shift in the trends for solving such problems, from expansion or elimination approach to the employment of heuristic algorithms. Although these heuristic algorithms are capable of providing a global optimal solution, their greatest drawback is the requirement of high computational effort. Because a highly efficient optimisation method is crucial for better accuracy and wider use, this paper presents an improved simulated annealing (SA) algorithm to solve the sensor placement problem. The algorithm is developed based on the sensor locations' coordinate system to allow for the searching in additional dimensions and to increase SA's random search performance while minimising the computation efforts. The proposed method is tested on a numerical slab model that consists of two hundred sensor location candidates using three types of objective functions; the determinant of the Fisher information matrix (FIM), modal assurance criterion (MAC), and mean square error (MSE) of mode shapes. Detailed study on the effects of the sensor numbers and cooling factors on the performance of the algorithm are also investigated. The results indicate that the proposed method outperforms conventional SA and Genetic Algorithm (GA) in the search for optimal sensor placement.

• Nuclear Engineering and Technology
• /
• v.55 no.5
• /
• pp.1630-1643
• /
• 2023

The correct situation awareness (SA) of operators is important for managing nuclear power plants (NPPs), particularly in accident-related situations. Among the three levels of SA suggested by Ensley, Level 3 SA (i.e., projection of the future status of the situation) is challenging because of the complexity of NPPs as well as the uncertainty of accidents. Hence, several prediction methods using artificial intelligence techniques have been proposed to assist operators in accident prediction. However, these methods only predict short-term plant status (e.g., the status after a few minutes) and do not provide information regarding the uncertainty associated with the prediction. This paper proposes an algorithm that can predict the multivariate and long-term behavior of plant parameters for 2 h with 120 steps and provide the uncertainty of the prediction. The algorithm applies bidirectional long short-term memory and an attention mechanism, which enable the algorithm to predict the precise long-term trends of the parameters with high prediction accuracy. A conditional variational autoencoder was used to provide uncertainty information about the network prediction. The algorithm was trained, optimized, and validated using a compact nuclear simulator for a Westinghouse 900 MWe NPP.

• IE interfaces
• /
• v.18 no.4
• /
• pp.370-381
• /
• 2005

This study is concerned with seeking the optimal allocation(disposition) for maximizing utility of consolidating old fashioned and new air defense weapon system like SAM-X(Patriot missile) and developing efficient solution algorithm based on simulated annealing(SA) algorithm. The SED(selection by effectiveness degree) procedure is implemented with an enhanced SA algorithm in which neighboring solutions could be generated only within the optimal feasible region by using a specially designed PERTURB function. Computational results conducted on the problem sets with a variety of size and parameters shows the significant efficiency of our SED algorithm over existing methods in terms of both the computation time and the solution quality.

• Proceedings of the KSRS Conference
• /
• 2002.10a
• /
• pp.559-564
• /
• 2002

This paper describes a new algorithm named as ray following algorithm which is applied for high-resolution satellite image simulation. The problems of the conventional ray tracing algorithm are pointed out especially when terrain elevations vary abruptly. The proposed algorithm follows the directional ray vector sequentially and thoroughly in order to determine the crossing point of the ray with the terrain surface. This way of sequential height comparison method is regarded as the only way to obtain accurate surface cross-section when a highly variant digital surface model is used. The experimental results show and compare the validities of the conventional and proposed algorithms.