• Journal of the Institute of Electronics Engineers of Korea TC
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• v.42 no.1
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• pp.17-27
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• 2005

In this paper, we introduce a Parallel Interference Canceller (PIC) based sorting method to improve performance in the MC-DS/CDMA environment. A conventional PIC estimates and subtracts out all of the MAI (Multiple Access Interference) for each user in parallel. The parallel process ensures the low delay for the detection of all users. Also this scheme requires more stages for having better performance. Since the performance of PIC is strongly related to the correct MAI estimation, we introduce the IC (Interference Cancellation) scheme to estimate the accurate weaker signal group than the desired signal using conventional PIC. The principle of the proposed receiver sorts in descending order by the strength of signal and subtracts the MAI of the strong interferers from the desired signal for the accurate estimate of the weaker signals. Following this, the proposed scheme cancels out the improved weaker interference from the desired signal, using the output of the pre-step. In this result, the proposed system obtains better BER performance than the conventional PIC because the accuracy of the strong signal is improved. However, a disadvantage exists in that the processing time has slightly longer delay than the PIC owing to the power sorting and the MAI estimation process. The system performance evaluates and compares other non-liner It according to the number of sub-carriers in the limited-bandwidth.

• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.2
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• pp.160-167
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• 2023

An INS is a composite navigation system providing "added value" so defined if work stations provide Multi-Function Displays(MFDs) integrating information and functions for navigational tasks. Even though the minimum requirements for an INS are defined by IMO performance standards, a generic list of the devices and functions that constitute an INS does not exist, so the configuration of the INS is different for each manufacturer, and guidelines based on users' perspectives are also insufficient. This study was conducted to enhance the usability of the INS by analyzing the information required by users according to the ship's operating status and tasks and effectively structuring it in the MFD of the INS. By analyzing INS-related international standards and manufacturers' component equipment lists, mandatory navigation information was selected and card sorting tests were conducted on ship operators with experience in using MFDs to group the information required for each INS task. The results of the study can serve as a basic guideline for manufacturers to structure information based on users' experience when designing products.

• Earthquakes and Structures
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• v.11 no.2
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• pp.347-369
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• 2016

The main objective of this paper is the robust multi-objective optimization design of semi-active tuned mass damper (STMD) system using genetic algorithms and fuzzy logic. For optimal design of this system, it is required that the uncertainties which may exist in the system be taken into account. This consideration is performed through the robust design optimization (RDO) procedure. To evaluate the optimal values of the design parameters, three non-commensurable objective functions namely: normalized values of the maximum displacement, velocity, and acceleration of each story level are considered to minimize simultaneously. For this purpose, a fast and elitist non-dominated sorting genetic algorithm (NSGA-II) approach is used to find a set of Pareto-optimal solutions. The torsional effects due to irregularities of the building and/or unsymmetrical placements of the dampers are taken into account through the 3-D modeling of the building. Finally, the comparison of the results shows that the probabilistic robust STMD system is capable of providing a reduction of about 52%, 42.5%, and 37.24% on the maximum displacement, velocity, and acceleration of the building top story, respectively.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.1
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• pp.1-20
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• 2018

Service composition in the Inter-Cloud raises new challenges that are caused by the different Quality of Service (QoS) requirements of the users, which are served by different geo-distributed Cloud providers. This paper aims to explore how to select and compose such services while considering how to reach high efficiency on cost and response time, low network latency, and high reliability across multiple Cloud providers. A new hybrid multi-objective evolutionary algorithm to perform the above task called LS-NSGA-II-DE is proposed, in which the differential evolution (DE) algorithm uses the adaptive mutation operator and crossover operator to replace the those of the Non-dominated Sorting Genetic Algorithm-II (NSGA-II) to get the better convergence and diversity. At the same time, a Local Search (LS) method is performed for the Non-dominated solution set F{1} in each generation to improve the distribution of the F{1}. The simulation results show that our proposed algorithm performs well in terms of the solution distribution and convergence, and in addition, the optimality ability and scalability are better compared with those of the other algorithms.

• Smart Structures and Systems
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• v.26 no.5
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• pp.545-558
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• 2020

A design method of a Multiple Tuned Mass Damper (MTMD) system is presented for wind induced vibration control of a cable-supported roof structure. Modal contribution analysis is carried out to determine the dominating modes of the structure for the MTMD design. Two MTMD systems are developed for two most dominating modes. Each MTMD system is composed of multiple TMDs with small masses spread at multiple locations with large responses in the corresponding mode. Frequencies of TMDs are distributed uniformly within a range around the dominating frequencies of the roof structure to enhance the robustness of the MTMD system against uncertainties of structural frequencies. Parameter optimizations are carried out by minimizing objective functions regarding the structural responses, TMD strokes, robustness and mass cost. Two optimization approaches are used: Single Objective Approach (SOA) using Sequential Quadratic Programming (SQP) with multi-start method and Multi-Objective Approach (MOA) using Non-dominated Sorting Genetic Algorithm-II (NSGA-II). The computation efficiency of the MOA is found to be superior to the SOA with consistent optimization results. A Pareto optimal front is obtained regarding the control performance and the total weight of the TMDs, from which several specific design options are proposed. The final design may be selected based on the Pareto optimal front and other engineering factors.

• Journal of the Korean Society for Precision Engineering
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• v.24 no.4 s.193
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• pp.84-92
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• 2007

Dynamic process planning requires not only more flexible capabilities of a CAPP system but also higher utility of the generated process plans. In order to meet the requirements, this paper develops an algorithm that can select machines for the machining operations by calculating the machine loads. The developed algorithm is based on the multi-objective genetic algorithm that gives rise to a set of optimal solutions (in general, known as the Pareto-optimal solutions). The objective is to satisfy both the minimization number of part movements and the maximization of machine utilization. The algorithm is characterized by a new and efficient method for nondominated sorting through K-means algorithm, which can speed up the running time, as well as a method of two stages for genetic operations, which can maintain a diverse set of solutions. The performance of the algorithm is evaluated by comparing with another multiple objective genetic algorithm, called NSGA-II and branch and bound algorithm.

• Steel and Composite Structures
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• v.52 no.1
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• pp.89-107
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• 2024

This article focuses on the static and dynamic analysis and optimization of an anisogrid lattice plate subjected to axial compressive load with simply supported boundary conditions. The lattice plate includes diagonal and transverse ribs and is modeled as an orthotropic plate with effective stiffness properties. The study employs the first-order shear deformation theory and the Ritz method with a Legendre approximation function. In the realm of optimization, the Non-dominated Sorting Genetic Algorithm-II is utilized as an evolutionary multi-objective algorithm to optimize. The research findings are validated through finite element analysis. Notably, this study addresses the less-explored areas of optimizing the geometric parameters of the plate by maximizing the buckling load and natural frequency while minimizing mass. Furthermore, this study attempts to fill the gap related to the analysis of the post-buckling behavior of lattice plates, which has been conspicuously overlooked in previous research. This has been accomplished by conducting nonlinear analyses and scrutinizing post-buckling diagrams of this type of lattice structure. The efficacy of the continuous methods for analyzing the natural frequency, buckling, and post-buckling of these lattice plates demonstrates that while a degree of accuracy is compromised, it provides a significant amount of computational efficiency.

• Journal of Electrical Engineering and Technology
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• v.6 no.6
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• pp.853-866
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• 2011

We propose a multi-objective space search algorithm (MSSA) and introduce the identification of fuzzy inference systems based on the MSSA and information granulation (IG). The MSSA is a multi-objective optimization algorithm whose search method is associated with the analysis of the solution space. The multi-objective mechanism of MSSA is realized using a non-dominated sorting-based multi-objective strategy. In the identification of the fuzzy inference system, the MSSA is exploited to carry out parametric optimization of the fuzzy model and to achieve its structural optimization. The granulation of information is attained using the C-Means clustering algorithm. The overall optimization of fuzzy inference systems comes in the form of two identification mechanisms: structure identification (such as the number of input variables to be used, a specific subset of input variables, the number of membership functions, and the polynomial type) and parameter identification (viz. the apexes of membership function). The structure identification is developed by the MSSA and C-Means, whereas the parameter identification is realized via the MSSA and least squares method. The evaluation of the performance of the proposed model was conducted using three representative numerical examples such as gas furnace, NOx emission process data, and Mackey-Glass time series. The proposed model was also compared with the quality of some "conventional" fuzzy models encountered in the literature.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.46 no.7
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• pp.527-534
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• 2018

The endurance of the multi-copter is one of the important variables that determine the mission performance. Therefore, accurate endurance should be defined as essential for performing effective missions. In this paper, we present the results of the study on the flight performance of the aircraft, especially the hovering of the drone(multi-copter). Unlike conventional aircraft, which consider aerodynamic performance by the fuselage, the multi-copter is mostly determined by the propulsion system. Therefore, the research method classifies the various parts constituting the drone system into functions, analyzes the performance of the unit parts and obtains the experimental data by sorting out the specifications and functions at the component level and mathematical formulation, The results of this study are as follows. In addition, the 5kg class quad copter was used to predict and verify the voltage change with endurance through analysis of in situ flight. By predicting endurance under various conditions, it can help design/build the right Multi-copter for mission.

• Proceedings of the KSME Conference
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• 2007.05b
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• pp.2690-2695
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• 2007

This work presents numerical optimization for design of a blade stacking line of a low speed axial flow fan with a fast and elitist Non-Dominated Sorting of Genetic Algorithm (NSGA-II) of multi-objective optimization using three-dimensional Navier-Stokes analysis. Reynolds-averaged Navier-Stokes (RANS) equations with ${\kappa}-{\varepsilon}$ turbulence model are discretized with finite volume approximations and solved on unstructured grids. Regression analysis is performed to get second order polynomial response which is used to generate Pareto optimal front with help of NSGA-II and local search strategy with weighted sum approach to refine the result obtained by NSGA-II to get better Pareto optimal front. Four geometric variables related to spanwise distributions of sweep and lean of blade stacking line are chosen as design variables to find higher performed fan blade. The performance is measured in terms of the objectives; total efficiency, total pressure and torque. Hence the motive of the optimization is to enhance total efficiency and total pressure and to reduce torque.