• 한국지능시스템학회:학술대회논문집
• /
• 한국퍼지및지능시스템학회 2003년도 ISIS 2003
• /
• pp.175-178
• /
• 2003

In recent years, several researchers have presented the extensive research reports on network optimization problems. In our real life applications, many important network problems are typically formulated as a Maximum flow model (MXF) or a Minimum Cost flow model (MCF). In this paper, we propose a Genetic Algorithm (GA) approach used a priority-based chromosome for solving the bicriteria network optimization problem including MXF and MCF models(MXF/MCF).

• International Journal of Computer Science & Network Security
• /
• 제21권1호
• /
• pp.40-48
• /
• 2021

Content-Based Image Retrieval (CBIR) system plays a vital role to retrieve the relevant images as per the user perception from the huge database is a challenging task. Images are represented is to employ a combination of low-level features as per their visual content to form a feature vector. To reduce the search time of a large database while retrieving images, a novel image retrieval technique based on feature dimensionality reduction is being proposed with the exploit of metaheuristic optimization techniques based on Genetic Algorithm (GA), Extended Binary Cuckoo Search (EBCS) and Whale Optimization Algorithm (WOA). Each image in the database is indexed using a feature vector comprising of fuzzified based color histogram descriptor for color and Median binary pattern were derived in the color space from HSI for texture feature variants respectively. Finally, results are being compared in terms of Precision, Recall, F-measure, Accuracy, and error rate with benchmark classification algorithms (Linear discriminant analysis, CatBoost, Extra Trees, Random Forest, Naive Bayes, light gradient boosting, Extreme gradient boosting, k-NN, and Ridge) to validate the efficiency of the proposed approach. Finally, a ranking of the techniques using TOPSIS has been considered choosing the best feature selection technique based on different model parameters.

• 한국강구조학회 논문집
• /
• 제18권2호
• /
• pp.147-160
• /
• 2006

본 논문에서는 개선소성힌지해석과 유전자 알고리듬을 이용한 평면 강골조 구조물의 퍼지최적설계 방법을 제시하였다. 개선소성힌지해석에서는 강골조 구조물의 기하학적 비선형성을 고려하기 위해 보-기둥 요소의 안정함수를 사용하였으며, 재료적 비선형을 고려하기 위해 잔류응력, 소성힌지, 그리고 기하학적 불완전성 등에 의한 점진적인 강성감소모델을 사용하였다. 유전자 알고리듬에서는 토너먼트 선택방법과 마이크로 유전자 알고리즘을 사용하였다. 목적함수로는 구조물의 총중량을 사용하였으며, 제약조건으로는 하중-저항능력, 사용성, 연성도, 그리고 시공성에 관한 기준을 고려하였다. 퍼지최적설계에서는 명확한 목적함수와 퍼지제약을 가지는 경우에 한하여 허용 오차는 제한값의 5%로 선택하고 비소속함수와 레벨컷 방법을 이용하여 0에서 1까지 0.2간격으로 나누어 최적화하였다. 여러 평면 강골조 구조물의 최적설계를 수행하여 일반GA최적설계와 퍼지GA최적설계의 최적값을 비교하였다.

• Computers and Concrete
• /
• 제6권3호
• /
• pp.253-268
• /
• 2009

This study aims to develop a cost-based high-performance concrete (HPC) mix optimization system based on an integrated approach using artificial neural networks (ANNs) and genetic algorithms (GA). ANNs are used to predict the three main properties of HPC, namely workability, strength and durability, which are used to evaluate fitness and constraint violations in the GA process. Multilayer back-propagation neural networks are trained using the results obtained from experiments and previous research. The correlation between concrete components and its properties is established. GA is employed to arrive at an optimal mix proportion of HPC by minimizing its total cost. A system prototype, called High Performance Concrete Mix-Design System using Genetic Algorithm and Neural Networks (HPCGANN), was developed in MATLAB. The architecture of the proposed system consists of three main parts: 1) User interface; 2) ANNs prediction models software; and 3) GA engine software. The validation of the proposed system is carried out by comparing the results obtained from the system with the trial batches. The results indicate that the proposed system can be used to enable the design of HPC mix which corresponds to its required performance. Furthermore, the proposed system takes into account the influence of the fluctuating unit price of materials in order to achieve the lowest cost of concrete, which cannot be easily obtained by traditional methods or trial-and-error techniques.

• 한국위성정보통신학회논문지
• /
• 제6권1호
• /
• pp.6-11
• /
• 2011

본 논문에서는 전기 배전시스템에서 부하단의 실시간 변화에 따른 배전시스템의 안정적인 운용을 가능하게 하기 위해서 유전자 알고리즘 방법을 사용한 방법에 대해서 연구하였다 배전시스템의 안정적인 운용은 각각의 배전 구역에서의 안정성을 향상시킨다는 중요한 장점을 가지고 있다 본 논문에서는 배전계통에서 가장 어려운 것으로 평가되는 접속절차에 대한 접근을 기반의 신뢰성 모델에 기초하여 수행하였다 유전자 알고리즘은 일반적인 생물계에서의 생존을 위한 진화의 과정을 구현한 것으로서 본 논문에서는 개의 노드와 개의 배전영역을 갖는 배전시스템을 대상으로 유전자 알고리즘을 적용한 배전시스템 최적화를 구현하였다.

• Journal of Mechanical Science and Technology
• /
• 제16권8호
• /
• pp.1033-1038
• /
• 2002

Genetic alsorithm (GA) , compared to the gradient-based optimization, has advantages of convergence to a global optimized solution. The genetic algorithm requires so many number of analyses that may cause high computational cost for genetic search. This paper proposes a personal computer network programming based on TCP/IP protocol and client-server model using socket, to improve processing speed of the genetic algorithm for optimization of composite laminated structures. By distributed processing for the generated population, improvement in processing speed has been obtained. Consequently, usage of network-based genetic algorithm with the faster network communication speed will be a very valuable tool for the discrete optimization of large scale and complex structures requiring high computational cost.

• 대한전기학회:학술대회논문집
• /
• 대한전기학회 2002년도 하계학술대회 논문집 D
• /
• pp.2146-2148
• /
• 2002

In this paper, PID control method using genetic algorithm to control the nonlinear multivariable system is presented. Genetic algorithms are global search techniques for nonlinear optimization. For experiment, the x-y rod balancing system with driver circuit board is fabricated. Experiments such as angle and position control for system are performed. The validity and control performance of the GA-based PID controller are confirmed by experimental results.

• 국제학술발표논문집
• /
• The 6th International Conference on Construction Engineering and Project Management
• /
• pp.114-116
• /
• 2015

This paper presents a Stochastic Time-Cost Tradeoff analysis system (STCT) that identifies optimal construction methods for activities, hence reducing the project completion time and cost simultaneously. It makes use of schedule information obtained from critical path method (CPM), applies alternative construction methods data obtained from estimators to respective activities, computes an optimal set of genetic algorithm (GA) parameters, executes simulation based GA experiments, and identifies near optimal solution(s). A test case verifies the usability of STCT.

• Electronic Materials Letters
• /
• 제14권6호
• /
• pp.784-792
• /
• 2018

In this letter, a standard deviation based optimization technique has been applied on High Resolution X-ray Diffraction symmetric and asymmetric scan results to accurately determine the Aluminum molar fraction and lattice relaxation of Molecular Beam Epitaxy grown compositionally graded Aluminum Gallium Nitride (AlGaN)/Aluminum Nitride/Gallium Nitride (GaN) heterostructures. Mathews-Blakeslee critical thickness model has been applied in an alternative way to determine the partially relaxed AlGaN epilayer thicknesses. The coupling coefficient determination has been presented in a different perspective involving sample tilt method by off set between the asymmetric planes of GaN and AlGaN. Sample tilt is further increased to determine mosaic tilt ranging between $0.01^{\circ}$ and $0.1^{\circ}$.

• International Journal of Aeronautical and Space Sciences
• /
• 제17권3호
• /
• pp.409-422
• /
• 2016

A parametric study based on an unsteady mathematical model of a pyrotechnically actuated device was performed for design optimization. The model simulates time histories for the chamber pressure, temperature, mass transfer and pin motion. It is validated through a comparison with experimentally measured pressure and pin displacement. Parametric analyses were conducted to observe the detailed effects of the design parameters using a validated performance analysis code. The detailed effects of the design variables on the performance were evaluated using the one-at-a-time (OAT) method, while the scatter plot method was used to evaluate relative sensitivity. Finally, the design optimization was conducted by employing a genetic algorithm (GA). Six major design parameters for the GA were chosen based on the results of the sensitivity analysis. A fitness function was suggested, which included the following targets: minimum explosive mass for the uniform ignition (small deviation), light casing weight, short operational time, allowable pyrotechnic shock force and finally the designated pin kinetic energy. The propellant mass and cross-sectional area were the first and the second most sensitive parameters, which significantly affected the pin's kinetic energy. Even though the peak chamber pressure decreased, the pin kinetic energy maintained its designated value because the widened pin cross-sectional area induced enough force at low pressure.