• International Journal of Fuzzy Logic and Intelligent Systems
• /
• 제16권4호
• /
• pp.281-292
• /
• 2016

The proposed scheme is based on the modified perturb and observe (P&O) algorithm combined with the sliding mode technique. A modified P&O algorithm based sliding mode controller is developed to study the effects of partial shade, temperature, and insolation on the performance of maximum power point tracking (MPPT) used in photovoltaic (PV) systems. Under partially shaded conditions and temperature, the energy conversion efficiency of a PV array is very low, leading to significant power losses. Consequently, increasing efficiency by means of MPPT is particularly important. Conventional techniques are easy to implement but produce oscillations at MPP. The proposed method is applied to a model to simulate the performance of the PV system for solar energy usage, which is compared to the conventional methods under non-uniform insolation improving the PV system utilization efficiency and allowing optimization of the system performance. The modified perturb and observe sliding mode controller successfully overcomes the issues presented by non-uniform conditions and tracks the global MPP. Compared to MPPT techniques, the proposed technique is more efficient; it produces less oscillation at MPP in the steady state, and provides more precise tracking.

• 한국지능시스템학회논문지
• /
• 제14권7호
• /
• pp.816-820
• /
• 2004

클러스터링은 데이터 집합을 유사한 데이터 개체들의 클러스터들로 분할하여 데이터 속에 존재하는 의미 있는 정보를 얻는 과정이다. 클러스터링의 주요 쟁점은 고차원 데이터를 효율적으로 클러스터링하는 것과 최적화 문제를 해결하는 것이다. 본 논문에서는 SVM(Support Vector Machines)기반의 새로운 유사도 측정법과 효율적으로 클러스터의 개수를 생성하는 방법을 제안한다. 고차원의 데이터는 커널 함수를 이용해 Feature Space로 매핑시킨 후 이웃하는 클러스터와의 유사도를 측정한다. 이미 생성된 클러스터들은 측정된 유사도 값과 Δd 임계값에 의해서 원하는 클러스터의 개수를 얻을 수 있다. 제안된 방법을 검증하기 위하여 6개의 UCI Machine Learning Repository의 데이터를 사용한 결과, 제시된 클러스터의 개수와 기존의 연구와 비교하여 향상된 응집도를 얻을 수 있었다.

• 한국지능시스템학회논문지
• /
• 제16권4호
• /
• pp.466-471
• /
• 2006

패턴 인식 문제에서 중요한 전처리 과정 중 하나는 특정을 선택하거나 추출하는 부분이다. 특정을 추출하는 방법으로는 PCA가 보통 사용되고 특정을 선택하는 방법으로는 SFS 나 SBS 등의 방법들이 자주 사용되고 있다. 본 논문은 진화 연산 방법으로써 비선형 최적화 문제에서 유용하게 사용되어 지고 있는 유전자 알고리즘을 특정 선택에 적용하는 유전자 알고리즘 특정 선택 (Genetic Algorithm Feature Selection: GAFS)방법을 개발하여 다른 특징 선택 알고리즘과의 비교를 통해 본 알고리즘의 성능을 관찰한다.

• Journal of Welding and Joining
• /
• 제23권4호
• /
• pp.41-47
• /
• 2005

Generally, the use of robots in manufacturing industry has been increased during the past decade. GMA(Gas Metal Arc) welding process is an actively Vowing area, and many new procedures have been developed for use with high strength alloys. One of the basic requirement for the automatic welding applications is to investigate relationships between process parameters and bead geometry. The objective of this paper is to develop a new approach involving the use of neural network and multiple regression methods in the prediction of bead geometry for GMA welding process and to develop an intelligent system that visualize bead geometry in order to employ the robotic GMA welding processes. Examples of the simulation for GMA welding process are supplied to demonstrate and verify the proposed system developed using MATLAB. The developed system could be effectively implemented not oかy for estimating bead geometry, but also employed to monitor and control the bead geometry in real time.

• 한국지능시스템학회논문지
• /
• 제20권6호
• /
• pp.780-785
• /
• 2010

본 논문은 물체인식이나 영상추적에 사용되는 컬러검출을 위한 GP(Genetic Programming) 기반의 컬러검출 모델을 제안한다. 기존의 컬러검출은 기본적인 RGB 모델에 대한 선형, 비선형 함수의 변환을 사용하거나, 최적화 기법이나 학습기법에 의해 조명 변화에 개선된 컬러 모델을 사용하고 있다. 하지만 대부분의 경우 색상 채널간의 간섭에 의해 다양한 색상에 대한 분류가 어렵고, 조명변화에 강인하지 못하다. 본 연구에서는 GP의 최적화된 학습기법과 모델 생성 기법을 통해 조명변화에 강인하고, 다중의 색상 검출이 가능하며, 파라미터 설정이 필요 없는 컬러 모델을 제안한다. 제안된 방법을 다양한 색상과 조명환경이 다른 영상에 대해서 기존 컬러모델과 비교 분석하였다.

• Computers and Concrete
• /
• 제32권6호
• /
• pp.577-594
• /
• 2023

Engineered cementitious composites with calcined clay limestone cement (LC³-ECC) as a kind of green, low-carbon and high toughness concrete, has recently received significant investigation. However, the complicated relationship between potential influential factors and LC³-ECC compressive strength makes the prediction of LC³-ECC compressive strength difficult. Regarding this, the machine learning-based prediction models for the compressive strength of LC³-ECC concrete is firstly proposed and developed. Models combine three novel meta-heuristic algorithms (golden jackal optimization algorithm, butterfly optimization algorithm and whale optimization algorithm) with support vector regression (SVR) to improve the accuracy of prediction. A new dataset about LC³-ECC compressive strength was integrated based on 156 data from previous studies and used to develop the SVR-based models. Thirteen potential factors affecting the compressive strength of LC³-ECC were comprehensively considered in the model. The results show all hybrid SVR prediction models can reach the Coefficient of determination (R²) above 0.95 for the testing set and 0.97 for the training set. Radar and Taylor plots also show better overall prediction performance of the hybrid SVR models than several traditional machine learning techniques, which confirms the superiority of the three proposed methods. The successful development of this predictive model can provide scientific guidance for LC³-ECC materials and further apply to such low-carbon, sustainable cement-based materials.

• 한국전자통신학회논문지
• /
• 제18권5호
• /
• pp.981-988
• /
• 2023

무인 비행체의 활용범위가 확대됨에 따라 관련 기술의 발전과 기술 수요도 증가하는 추세이다. 무인 비행체의 운영빈도가 늘어나고 운영의 편리성이 강조됨에 따라 관련 자율비행 기술도 중요성이 주목받고 있다. 무인 비행체의 자율 비행에 있어 목적지에 도달하는 경로계획을 세우는 일은 유도제어에서 중요하며 무인화의 효과를 극대화하기 위해서는 경로계획 역시 자동으로 생성하는 기술이 필요하다. 본 논문에서는 무인 비행체의 자율운영 효과를 높이기 위해서 급속탐색랜덤트리기법으로 생성된 경로를 무인기의 특성에 맞게 최적화하는 기법에 관한 연구를 수행하였다. 최적 거리, 최단 시간, 임무점 통과 등의 지표를 달성하기 위해 경로계획을 무인 비행체의 임무 목표와 동적 특성을 고려하여 최적화하였다. 제안한 기법은 장애물 상황에 대한 성능검증을 통해 무인 비행체 경로계획 생성에 적용 가능성을 확인하였다.

• Smart Structures and Systems
• /
• 제29권3호
• /
• pp.433-444
• /
• 2022

Concrete is a most utilized material in the construction industry that have main components. The strength of concrete can be improved by adding some admixtures. Evaluating the impact of fly ash (FA) and silica fume (SF) on the long-term compressive strength (CS) of concrete provokes to find the significant parameters in predicting the CS, which could be useful in the practical works and would be extensible in the future analysis. In this study, to evaluate the effective parameters in predicting the CS of concrete containing admixtures in the long-term and present a fitted equation, the multivariate adaptive regression splines (MARS) method has been used, which could find a relationship between independent and dependent variables. Next, for optimizing the output equation, biogeography-based optimization (BBO), particle swarm optimization (PSO), and hybrid PSOBBO methods have been utilized to find the most optimal conclusions. It could be concluded that for CS predictions in the long-term, all proposed models have the coefficient of determination (R²) larger than 0.9243. Furthermore, MARS-PSOBBO could be offered as the best model to predict CS between three hybrid algorithms accurately.

• IEIE Transactions on Smart Processing and Computing
• /
• 제5권5호
• /
• pp.349-357
• /
• 2016

The era of the Internet of Things (IoT) is upon us. In this era, minimizing power consumption becomes a primary concern for system-on-chip designers. While traditional power minimization and dynamic power management (DPM) techniques have been heavily explored to improve the power efficiency of devices inside very large-scale integration (VLSI) platforms, there is one critical factor that is often overlooked, which is the power conversion efficiency of a power delivery network (PDN). This paper is a tutorial that focuses on the power conversion efficiency of the PDN, and introduces novel methods to improve it. Circuit-, architecture-, and system-level approaches are presented to optimize PDN designs, while case studies for three different VSLI platforms validate the efficacy of the introduced approaches.

• 한국군사과학기술학회지
• /
• 제11권3호
• /
• pp.89-98
• /
• 2008

The vetronics is necessarily required for enhancement of the operational capability and optimization of the system architecture. In this paper, we presents the realtime control methods for the vetronics of the fighting vehicles. We proposed the data distribution based on standard bus and computer resource for realtime and integrated control of the system. Embedded computers are designed considering extensibility and reliability of the system. The integrated display improves the operator's capability. We applied the network centric battle management and digital power control with intelligent switching elements to increase cooperated combat efficiency and reliability. To show the feasibility of the presented design schemes, the vetronics has been implemented and applied to a real fighting vehicle.