• 한국전기전자재료학회:학술대회논문집
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• 한국전기전자재료학회 2003년도 하계학술대회 논문집 Vol.4 No.1
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• pp.58-62
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• 2003

Silicon carbide (SiC) was etched in a $NF_3/CH_4$ inductively coupled plasma. The etch process was modeled by using a neural network called generalized regression neural network (GRNN). For modeling, the process was characterized by a $2^4$ full factorial experiment with one center point. To test model appropriateness, additional test data of 16 experiments were conducted. Particularly, the GRNN predictive capability was drastically improved by a genetic algorithm (GA). This was demonstrated by an improvement of more than 80% compared to a conventionally obtained model. Predicted model behaviors were highly consistent with actual measurements. From the optimized model, several plots were generated to examine etch rate variation under various plasma conditions. Unlike the typical behavior, the etch rate variation was quite different depending on the bias power Under lower bias powers, the source power effect was strongly dependent on induced dc bias. The etch rate was strongly correated to the do bias induced by the gas ratio. Particularly, the etch rate variation with the bias power at different gas ratio seemed to be limited by the etchant supply.

• 한국지능시스템학회논문지
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• 제18권4호
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• pp.555-561
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• 2008

GA 기반의 4족 보행로봇의 걸음새의 속도와 안정성을 최적화하는 걸음새의 자동 생성 방법을 구현한다. 기존에 사용된 걸음새 파라미터 집합에서 중요 파라미터의 영향을 분석하였고, 이를 통해 효율적인 탐색 방향을 설정하였다. 또한 속도 위주의 기존 연구와는 달리 반 정확도가 수반된 결과를 얻도록 하였다. 제안된 기법의 검증을 위하여 SONY Aibo 4족 보행 로봇에 대해서 ODE 기반의 물리적 특성을 포함한 정교한 시뮬레이션이 가능한 Webots 을 이용하여 실험을 수행하였고, 속도와 안정성 면에서 향상된 결과를 얻었다.

• 드라이브 ㆍ 컨트롤
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• 제15권4호
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• pp.74-80
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• 2018

A damper is a hydraulic device designed to absorb or eliminate shock impulses which is acting on the sprung mass of vehicle. It converting the kinetic energy of the shock into another form of energy, typically heat. In a vehicle, a damper reduce vibration of car, leading to improved ride comfort and running stability. Therefore, a damper is one of the most important components in a vehicle suspension system. Conventionally, the design process of vehicle suspensions has been based on trial and error approaches, where designers iteratively change the values of the design variables and reanalyze the system until acceptable design criteria are achieved. Therefore, the ability to tune a damper properly without trial and error is of great interest in suspension system design to reduce time and effort. For this reason, a many previous researches have been done on modeling and simulation of the damper. In this paper, we have conducted optimal design process to find optimal design parameters of damping force which minimize a acceleration of sprung mass for a given suspension system using genetic algorithm.

• Computers and Concrete
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• 제27권4호
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• pp.305-317
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• 2021

The bond between the concrete and bar is a main factor affecting the performance of the reinforced concrete (RC) members, and since the steel corrosion reduces the bond strength, studying the bond behavior of concrete and GFRP bars is quite necessary. In this research, a database including 112 concrete beam test specimens reinforced with spliced GFRP bars in the splitting failure mode has been collected and used to estimate the concrete-GFRP bar bond strength. This paper aims to accurately estimate the bond strength of spliced GFRP bars in concrete beams by applying three soft computing models including multivariate adaptive regression spline (MARS), Kriging, and M5 model tree. Since the selection of regularization parameters greatly affects the fitting of MARS, Kriging, and M5 models, the regularization parameters have been so optimized as to maximize the training data convergence coefficient. Three hybrid model coupling soft computing methods and genetic algorithm is proposed to automatically perform the trial and error process for finding appropriate modeling regularization parameters. Results have shown that proposed models have significantly increased the prediction accuracy compared to previous models. The proposed MARS, Kriging, and M5 models have improved the convergence coefficient by about 65, 63 and 49%, respectively, compared to the best previous model.

• International Journal of Computer Science & Network Security
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• 제21권3호
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• pp.145-152
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• 2021

In the Recent times, various technological enhancements in the field of artificial intelligence and big data has been noticed. This advancement coupled with the evolution of the 5G communication and Internet of Things technologies, has helped in the development in the domain of smart mine construction. The development of unmanned vehicles with enhanced and smart scheduling system for open-pit mine transportation is one such much needed application. Traditional open-pit mining systems, which often cause vehicle delays and congestion, are controlled by human authority. The number of sensors has been used to operate unmanned cars in an open-pit mine. The sensors haves been used to prove the real-time data in large quantity. Using this data, we analyses and create an improved transportation scheduling mechanism so as to optimize the paths for the vehicles. Considering the huge amount the data received and aggregated through various sensors or sources like, the GPS data of the unmanned vehicle, the equipment information, an intelligent, and multi-target, open-pit mine unmanned vehicle schedules model was developed. It is also matched with real open-pit mine product to reduce transport costs, overall unmanned vehicle wait times and fluctuation in ore quality. To resolve the issue of scheduling the transportation, we prefer to use algorithms based on artificial intelligence. To improve the convergence, distribution, and diversity of the classic, rapidly non-dominated genetic trial algorithm, to solve limited high-dimensional multi-objective problems, we propose a decomposition-based restricted genetic algorithm for dominance (DBCDP-NSGA-II).

• Journal of Information Processing Systems
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• 제18권3호
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• pp.374-388
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• 2022

Database systems usually have many parameters that must be configured by database administrators and users. RocksDB achieves fast data writing performance using a log-structured merged tree. This database has many parameters associated with write and space amplifications. Write amplification degrades the database performance, and space amplification leads to an increased storage space owing to the storage of unwanted data. Previously, it was proven that significant performance improvements can be achieved by tuning the database parameters. However, tuning the multiple parameters of a database is a laborious task owing to the large number of potential configuration combinations. To address this problem, we selected the important parameters that affect the performance of RocksDB using random forest. We then analyzed the effects of the selected parameters on write and space amplifications using analysis of variance. We used a genetic algorithm to obtain optimized values of the major parameters. The experimental results indicate an insignificant reduction (-5.64%) in the execution time when using these optimized values; however, write amplification, space amplification, and data processing rates improved considerably by 20.65%, 54.50%, and 89.68%, respectively, as compared to the performance when using the default settings.

• 지구물리
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• 제9권4호
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• pp.321-331
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• 2006

최근 급격한 인구증가와 산업화, 도시화로 포장지역의 증가에 따른 불투수지역의 증가로 유역의 유출 특성의 변화를 유발시키고 있다. 도시화 유역의 효율적인 관리를 위해서는 유역에 대한 정확한 지형인자 및 수문관련 인자들이 추출되어야 함에 따라 본 연구에서는 지리정보체계와 유전자알고리즘의 결합을 통하여 입력정보의 정확성을 향상시키고, 매개변수를 추정하였다. 이러한 목적에 따라 본 연구에서는 전형적인 한국의 도시화하천으로서 본류와 상류로부터 오전천, 당정천 등의 지류를 지니고 있는 안양천을 연구대상으로 선정하여 유출량 해석에 XP-SWMM을 적용하였고, 이의 적용과정을 개선하기 위하여 지리정보체계와 유전자 알고리즘을 적용하였다. XP-SWMM 매개변수들의 민감도 분석을 통하여 도시 유출의 거동특성을 조사하였으며, 이를 바탕으로 매개변수들의 개선규칙을 설정하였고 이러한 규칙 및 사실등을 통하여 유전자 알고리즘을 구성하였다. GIS를 이용하여 지형도로부터 각각의 소유역에 대하여 면적, 경사도, 유역폭 등 수문정보를 얻었고, 토지이용도와 토양도로부터 불투수비, 토지이용상태, 침투능에 대한 정보를 얻었다. 도시유출 모형인 XP-SWMM을 선택하여 모의 후 민감도 분석을 통해 선정된 매개변수에 대하여 보정은 자동보정으로 무작위 탐색법의 일종인 유전자알고리즘(Genetic Algorithm, GA)을 사용하여 매개변수들을 추정하였고, 이의 적용성을 확인하였다.

• 한국지능정보시스템학회:학술대회논문집
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• 한국지능정보시스템학회 2000년도 춘계정기학술대회 e-Business를 위한 지능형 정보기술 / 한국지능정보시스템학회
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• pp.343-346
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• 2000

In this paper, a novel approach to intruder detection is introduced. The approach, based on the genetic algorithms, improved detection rate of the host systems which has traditionally relied on known intruder patterns and host addresses. Rather than making judgments on whether the access is instrusion or not, the systems can continuously monitor systems with categorized security level. With the categorization, when the intruder attempts repeatedly to access the systems, the security level is incrementally escalated. In the simulation of a simple intrusion, it was shown that the current approach improves robustness of the security systems by enhancing detection and flexibility. The evolutionary approach to intruder detection enhances adaptability of the system.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1999년도 하계학술대회 논문집 B
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• pp.924-926
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• 1999

To reduce chattering in sliding mode control, a boundary layer around the sliding surface is used, and a continuous control is applied within the boundary. In this paper, a method of determining the sliding mode controller switching gains and the width of boundary layer is presented. Contrary to the trial and error selection of the switching gains and the width of boundary layer, the selection in the presented work is done using genetic algorithms. Simulation results show that the system performance has been improved.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2006년도 춘계학술대회논문집
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• pp.164-170
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• 2006

본 연구는 유전 알고리듬, 타부탐색법 그리고 반응표면법등 최근 많이 사용하고 있는 프로그램들의 장점들을 결합한 새로운 조합 유전 알고리듬을 제안한다. 본 알고리듬은 반응표면법 및 심플렉스법을 사용하여 유전알고리듬의 약점으로 여겨지는 수렴속도를 항상시키도록 하였다. 또한 유전 알고리듬에서 램덤한 다양성을 제공하지만, 본 연구에서는 타부리스트를 이용하여 체계적인 다양성을 추구하도록 하였다. 그리고 전통적인 시험함수에 본 알고리듬을 적용함으로써 본 방법의 효율성을 입증하였고 그 결과를 유전 알고리듬의 결과와 비교하였다. 또한 새롭게 제안된 알고리듬을 선미부에 위치한 청수탱크의 중량최적화에 적용한 길과 전역최적해를 효율적으로 찾는 것을 입증하였다. 또한 반응표면법을 사용한 새로운 유전알고리듬의 경우 실제 추가적인 목적함수를 평가하기 위한 계산이 필요 없으므로 수렴속도가 일반 유전 알고리듬보다 향상 되었음을 알 수 있었다. 마지막으로 제안된 조합 유전 알고리듬은 전역탐색능력과 수렴속도 측면에서 매우 강력한 전역 최적화 알고리듬임을 알 수 있었다.