• 한국신재생에너지학회:학술대회논문집
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• 한국신재생에너지학회 2005년도 춘계학술대회
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• pp.349-352
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• 2005

The energy management of an HEV using optimal control and global optimization is thought to be closest to the best operation of the system. However, there are some controversies on the ways of defining the optimization problems and constituting the optimal control simulators. Here, we presented a simulator which adopts the concept of equivalent fuel economy and leads the vehicle to run in a more efficient way. In order to realize the optimal operation of the HEV and check the validity of the control logics, we also developed a forward-facing simulator. The simulator was developed with the Cruise and MATLAB co-simulation interface. Especially, neural network controller was used for the hybrid control module in the simulator. With the simulator, the optimal operation could be converted into hybrid control rules and the validity of the operation was verified.

• 한국신재생에너지학회:학술대회논문집
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• 한국신재생에너지학회 2006년도 추계학술대회
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• pp.97-100
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• 2006

Accelerating ability is one of the most important performance of the vehicle. Unlike conventional internal combustion vehicles and power-assist hybrid vehicles, the maximized acceleration of dual mode hybrid vehicles is not simply. achieved by maximizing engine or motor torque Because of the dynamic stability of planetary gear, speeds and torques control of engine, motor 1 and motor 2 is essential and according to control value, acceleration performance is changed There are two control values which are velocity and torque for each component totalling six. These six values can be variables for an objective function. However, because three velocity variables can be regarded as only one variable speed ratio and the remaining three torque variables can be solved analytically, without complicated numerical algorithm the solution for the objective function can be obtained. This optimized solution shows the best performance possible to the specified dual mode system.

• Journal of Electrical Engineering and Technology
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• 제12권4호
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• pp.1511-1518
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• 2017

Renewable energy hybrid systems look into the process of choosing the finest arrangement of components and their sizing with suitable operation approach to deliver effective, consistent and cost effective energy source. This paper presents hybrid renewable energy system (HRES) solar photovoltaic, downdraft biomass gasifier, and fuel cell based generation system. HRES electrical power to supply the electrical load demand of academic research building sited in $23^{\circ}12^{\prime}N$ latitude and $77^{\circ}24^{\prime}E$ longitude, India. Fuzzy logic programming discover the most effective capital and replacement value on components of HRES. The cause regarding fuzzy logic rule usage on HOMER pro (Hybrid optimization model for multiple energy resources) software program finds the optimum performance of HRES. HRES is designed as well as simulated to average energy demand 56.52 kWh/day with a peak energy demand 4.4 kW. The results shows the fuel cell and battery bank are the most significant modules of the HRES to meet load demand at late night and early morning hours. The total power generation of HRES is 23,794 kWh/year to the supply of the load demand is 20,631 kWh/year with 0% capacity shortage.

• Structural Engineering and Mechanics
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• 제65권6호
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• pp.707-719
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• 2018

In this article, a new method is introduced to improve the local search capability of meta-heuristic algorithms using the projection of the path on the border of constraints. In a mathematical point of view, the Gradient Projection Method is applied through a new approach, while the imposed limitations are removed. Accordingly, the gradient vector is replaced with a new meta-heuristic based vector. Besides, the active constraint identification algorithm, and the projection method are changed into less complex approaches. As a result, if a constraint is violated by an agent, a new path will be suggested to correct the direction of the agent's movement. The presented procedure includes three main steps: (1) the identification of the active constraint, (2) the neighboring point determination, and (3) the new direction and step length. Moreover, this method can be applied to some meta-heuristic algorithms. It increases the chance of convergence in the final phase of the search process, especially when the number of the violations of the constraints increases. The method is applied jointly with the authors' newly developed meta-heuristic algorithm, entitled Star Graph. The capability of the resulted hybrid method is examined using the optimal design of truss and frame structures. Eventually, the comparison of the results with other meta-heuristics of the literature shows that the hybrid method is successful in the global as well as local search.

• 한국연소학회:학술대회논문집
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• 한국연소학회 2012년도 제44회 KOSCO SYMPOSIUM 초록집
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• pp.199-200
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• 2012

An experimental study on geometric optimization was conducted to develop a hybrid/dual swirl jet combustor for a micro-gas turbine. A hybrid concept indicating a combination of swirling jet partially premixed and premixed flames were adopted to achieve high flame stability as well as clean combustion. Location of pilot nozzle, angle and direction of swirl vane were varied as main parameters with a constant fuel flow rate for each nozzle. The results showed that the variation in location of pilot nozzle resulted in significant change in swirl intensity due to the change in flow area near burner exit, and thus, optimized nozzle location was determined on the basis of CO and NOx emissions under conditions of co-swirl flow and swirl $angle=30^{\circ}$. The increase in swirl angle (from $30^{\circ}$ to $45^{\circ}$) enhanced the emission performances, in particular, with a significant reduction of CO emission near lean-flammability limit. It was observed that the CO emission near lean-flammability limit was further reduced through the counter-swirl flow. However, there was not significant change in the NOx emission in the operating conditions (i.e. equivalence ratio of 0.6~0.7) between the co- and the counter-swirl flow.

• Geomechanics and Engineering
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• 제1권1호
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• pp.85-96
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• 2009

The radius and coordinate of sliding circle are taken as searching variables in slope stability analysis. Genetic algorithm is applied for searching for critical factor of safety. In order to search for critical factor of safety in slope stability analysis efficiently and in a robust manner, some improvements for simple genetic algorithm are proposed. Taking the advantages of efficiency of neighbor-search of the simulated annealing and the robustness of genetic algorithm, a hybrid optimization method is presented. The numerical computation shows that the procedure can determine the minimal factor of safety and be applied to slopes with any geometry, layering, pore pressure and external load distribution. The comparisons demonstrate that the genetic algorithm provides a same solution when compared with elasto-plastic finite element program.

• ETRI Journal
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• 제43권2호
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• pp.260-271
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• 2021

This paper addresses Very large-scale integration (VLSI) placement optimization, which is important because of the rapid development of VLSI design technologies. The goal of this study is to develop a hybrid algorithm for VLSI placement. The proposed algorithm includes a sequential combination of a genetic algorithm and an evolutionary algorithm. It is commonly known that local search algorithms, such as random forest, hill climbing, and variable neighborhoods, can be effectively applied to NP-hard problem-solving. They provide improved solutions, which are obtained after a global search. The scientific novelty of this research is based on the development of systems, principles, and methods for creating a hybrid (combined) placement algorithm. The principal difference in the proposed algorithm is that it obtains a set of alternative solutions in parallel and then selects the best one. Nonstandard genetic operators, based on problem knowledge, are used in the proposed algorithm. An investigational study shows an objective-function improvement of 13%. The time complexity of the hybrid placement algorithm is O(N2).

• 대한기계학회논문집B
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• 제39권1호
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• pp.71-78
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• 2015

본 논문에서는 복합발전시스템을 구성하는 각 단위 구성품의 교체비용이 변화할 때 각 단위 구성품의 용량 및 전체시스템의 경제성이 얼마나 변화하는지를 나타내는 민감도 분석을 수행하는 방법을 제시한다. 민감도 분석에는 복합발전시스템 경제 분석용 툴인 HOMER를 이용한다. 민감도 분석을 통해 교체비용 변화에 대해 민감도가 높은 구성품의 비중이 최소화 되게 설계하거나 예상되는 가격변동을 사전에 고려함으로써 복합발전시스템의 경제성을 최적화할 수 있으며, 민감도가 높은 구성품의 비중을 낮추기 위한 다른 조합의 복합 발전시스템 구성에 대한 정보도 제공할 수 있다. 민감도 분석의 예로서 주택용 부하 모델에 대해 HOMER에서 제공되는 일반적인 데이터를 사용하여 각 구성품 교체비용에 대한 용량 및 경제성 민감도를 정량적으로 분석하였다.

• 해양환경안전학회:학술대회논문집
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• 해양환경안전학회 2018년도 공동국제학술발표회
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• pp.194-194
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• 2018

• 지능정보연구
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• 제3권2호
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• pp.11-22
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• 1997

본 연구에서는 비선형 최적화 문제를 효율적으로 해결하기 위한 혼합유전알고리즘(Hybrid Genetic Algorthm : HGA)을 개발하였다. HGA는 기존 유전알고리즘의 적용에 있어 문제점으로 지적된 정밀도의 적용문제와 벌금함수의 사용을 배제하였으며 지역적최적점으로 빠르게 수렴하는 기존의 지역적 탐색법과 유전알고리즘 적용이후 수렴된 해 주변에 대한 정밀탐색법을 함께 고려하여 설계하였으며 이를 세가지의 비선형 최적화 문제 적용하여 본 논문에서 개발한 HGA의 유효성을 보였다.