• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.31 no.1 s.256
• /
• pp.26-35
• /
• 2007

The vehicle of urban transit is a complex system that consists of various electric, electronic, and mechanical equipments, and the maintenance cost of this complex and large-scale system generally occupies sixty percent of the LCC (Life Cycle Cost). For reasonable establishing of maintenance strategies, safety security and cost limitation must be considered at the same time. The concept of system reliability has been introduced and optimized as the key of reasonable maintenance strategies. For optimization, three preceding studies were accomplished; standardizing a maintenance classification, constructing RBD (Reliability Block Diagram) of VVVF (Variable Voltage Variable Frequency) urban transit, and developing a web based reliability evaluation system. Historical maintenance data in terms of reliability index can be derived from the web based reliability evaluation system. In this paper, we propose applying inverse problem analysis method and hybrid neuro-genetic algorithm to system reliability optimization for using historical maintenance data in database of web based system. Feed-forward multi-layer neural networks trained by back propagation are used to find out the relationship between several component reliability (input) and system reliability (output) of structural system. The inverse problem can be formulated by using neural network. One of the neural network training algorithms, the back propagation algorithm, can attain stable and quick convergence during training process. Genetic algorithm is used to find the minimum square error.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.39 no.1
• /
• pp.56-63
• /
• 2016

We consider a satellite mission scheduling problem, which is a promising problem in recent satellite industry. This problem has various considerations such as customer importance, due date, limited capacity of energy and memory, distance of the location of each mission, etc. Also we consider the objective of each satellite such as general purpose satellite, strategic mission and commercial satellite. And this problem can be modelled as a general knapsack problem, which is famous NP-hard problem, if the objective is defined as to maximize the total mission score performed. To solve this kind of problem, heuristic algorithm such as taboo and genetic algorithm are applied and their performance are acceptable in some extent. To propose more efficient algorithm than previous research, we applied a particle swarm optimization algorithm, which is the most promising method in optimization problem recently in this research. Owing to limitation of current study in obtaining real information and several assumptions, we generated 200 satellite missions with required information for each mission. Based on generated information, we compared the results by our approach algorithm with those of CPLEX. This comparison shows that our proposed approach give us almost accurate results as just less than 3% error rate, and computation time is just a little to be applied to real problem. Also this algorithm has enough scalability by innate characteristic of PSO. We also applied it to mission scheduling problem of various class of satellite. The results are quite reasonable enough to conclude that our proposed algorithm may work in satellite mission scheduling problem.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.17 no.4
• /
• pp.797-804
• /
• 2013

This paper presents an efficient design method of multiplierless 2-D state space digital filter based on a particle swarm optimization(PSO) algorithm. The design task is reformulated as a constrained minimization problem and is solved by our newly developed PSO algorithm. To ensure the stability of the designed 2-D state space digital filters, a stability strategy is embedded in the basic PSO algorithm. The superiority of the proposed method is demonstrated by several experiments. The results show that the approximation error and roundoff noise of the resultant filters are better than those of the digital filters which designed by recently published filter design methods. In addition, the designed filters with power-of-two coefficients have only about 1/4 computational burden of the 2-D digital filters designed in the 2's complement binary representation.

• Journal of Broadcast Engineering
• /
• v.13 no.5
• /
• pp.719-731
• /
• 2008

This paper defines QoE (Quality of Experience) for multi-view video streaming service over WiBro and proposes the CLO (Cross-Layer Optimization) algorithm can maximize this. Proposal CLO algorithm contains from physical layer to video layer. Under the time-varying wireless channel condition, the CLO technique takes view-wise and the temporal priority of the multi-view video into consideration in order to decide the transmission of frames and its FEC level. At the handover situation, it is shown through computer simulation that the optimal quality of the multi-view video can be achieved using the minimum amount of resources if the proposed CLO technique is applied.

• Archives of Pharmacal Research
• /
• v.23 no.5
• /
• pp.507-512
• /
• 2000

This study set out to improve the physical and pharmaceutical characteristics of the present formulation using an appropriate experimental design. The work described here concerns the formulation of the dispersible tablet applying direct compression method containing roxithromycin in the form of coated granules. In this study $2^3$ factorial design was used as screening test model and Central Composite Design (CCC) associated with response surface methodology was used as optimization study model to develop and to optimize the proper formulation of roxithromycin dispersible tablet. The three independent variables investigated were functional excipients like binder (X1), disintegrant (X2) and lubricant (X3). The effects of these variables were investigated on the following responses: hardness (Y1), friability (Y2) and disintegration time (Y3) of tablet. Three replicates at the center levels of the each design were used to independently calculate the experimental error and to detect any curvature in the response surface. This enabled the best formulations to be selected objectively. The effect order of each term to all response variable was X3> X2> Xl> X1＊X2> X2＊X2> X2＊X3> X3＊X3> Xl＊X3> Xl＊Xl and model equations on each response variables were generated. Optimized compositions of formula were accordingly computed using those model equations and confirmed by following demonstration study. As a result, this study has demonstrated the efficiency and effectiveness of using a systematic formulation optimization process to develop the tablet formulation of roxithromycin dispersible tablet with limited experiment.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
• /
• v.22 no.1
• /
• pp.40-49
• /
• 2008

Interior permanent magnet synchronous motor(IPMSM) has become a popular choice in electric vehicle applications and so of due to their excellent power to weight ratio. To obtain maximum efficiency in these applications, this paper proposes the neural network control method. The controllable electrical loss which consists of the copper loss and the iron loss can be minimized by the error back propagation algorithm(EBPA) of neural network. The minimization of loss is possible to realize eHciency optimization control for the IPMSM drive. This paper proposes high performance and robust control through a real time calculation of parameter variation such as variation of back emf constant, armature resistance and d-axis inductance about the motor operation. Proposed algorithm is applied IPMSM drive system, prove validity through analysis operating characteristics con011ed by efficiency optimization control.

• Journal of the Computational Structural Engineering Institute of Korea
• /
• v.21 no.5
• /
• pp.413-419
• /
• 2008

Deterministic design optimization (DO) does not explicitly deal with a variety of factors from inherent randomness and uncertainties. Reliability based design optimization(RBDO) is necessary to use in engineering systems in order to guarantee quality and performance of product. In this paper, design variables are considered as random variables. Standard deviation according to change of design variables have changed as much as coefficient of variation. And, if the standard deviation is error of manufacturing, standard deviation-mean relation is concave form. We obtain reliability index using advanced first order second moment method(AFOSM). This paper is examined by solving two examples and the results are compares with DO, RBDO and suggested RBDO.

• Proceedings of the KSME Conference
• /
• 2001.06b
• /
• pp.501-506
• /
• 2001

Computer modeling is essential to evaluate possible design of suspension for a railway vehicles. By creating a simulation, the engineers are able to assess the feasibility of a given design and change the design factors to get a better design. But if one wishes to perform complex analysis on the simulation, such as railway vehicle dynamic, the computational time can become overwhelming. Therefore, many researchers have turned to surrogate modeling. A surrogate model is essentially a regression performed on a data sampling of the simulation. In the most general sense, metamodels(surrogate model) take the form $y(x)=f(x)+{\varepsilon}$, where y(x) is the true simulation output, f(x) is the metamodel output, and $\varepsilon$ is the error between the two. In this paper, a second order polynomial equation is partially used as a metamodel to represent the forty-six dynamic performances for high speed train. The number of factors as design variables of the metamodel is twenty-nine, which are composed the dynamic characteristics of suspension. This metamodel is used to search the optimum values of suspension characteristics which minimize the dynamic responses for high speed train. This optimization is a multi-objective problem which have many design variables. This paper shows that the response surface model which is made through the design of analysis of computer experiments method is very efficient to solve this complex optimization problem.

• Journal of Korean Association for Spatial Structures
• /
• v.10 no.4
• /
• pp.113-122
• /
• 2010

Space frame structures are included in the large spatial structures and can adopt various structure types. But, it is not easy to choose the optimal member size and shape because it depends on the structural engineer's experience and the repeated trial and error. Therefore, in this study, the final goal is to help the designer with the selection of the optimum shape. First, various space frame structures with ellipse dome and vault complex types are chosen and the shape generation method is considered to generate the nodes, coordinates and members. In optimal design process of space frame structure, each node coordinate changes according to height variation or the number of rings. Therefore, the auto generation technique of nodes and members is required in order to consider this phenomenon in optimal design process. Next, the shape generation module is created, base on the shape generation method. This module is connected with the analysis module and the optimization algorithm. Finally, the example model is presented for the evaluation of the efficiency of optimization algorithms.

• Journal of the Korea Institute of Military Science and Technology
• /
• v.23 no.4
• /
• pp.407-416
• /
• 2020

Recent complex battle field demands Network Centric Warfare(NCW) ability to control various parts into a cohesive unit. In path planning filed, the NCW ability increases complexity of path planning algorithm, and it has to consider a communication coverage map as well as traditional parameters such as minimum radar exposure and survivability. In this paper, pros and cons of various propagation models are summarized, and we suggest a coverage map generation method using a Longley-Rice propagation model. Previous coverage map based on line of sight has significant discontinuities that limits selection of path planning algorithms such as Dijkstra and fast marching only. If there is method to remove discontinuities in the coverage map, optimization based path planning algorithms such as trajectory optimization and Particle Swarm Optimization(PSO) can also be used. In this paper, the Longley-Rice propagation model is used to calculate continuous RF strengths, and convert the strength data using smoothed leaky BER for the coverage map. In addition, we also suggest other types of rough coverage map generation using a lookup table method with simple inputs such as terrain type and antenna heights only. The implemented communication coverage map can be used various path planning algorithms, especially in the optimization based algorithms.