• 한국소음진동공학회:학술대회논문집
• /
• 한국소음진동공학회 1996년도 춘계학술대회논문집; 부산수산대학교, 10 May 1996
• /
• pp.125-129
• /
• 1996

This paper deals with the problem of placement/sizing of distributed piezo actuators to achieve the control objective of vibration suppression. Using the mean square response as a performance index in optimization, we obtain optimal placement and sizing of the actuator. The use of genetic algorithms as a technique for solving optimization problems of placement and sizing is explored. Genetic algorithms are also used for the control strategy. The analysis of the system and response moment equations are carried out by using the Fokker-Planck equation. This paper presents the design and analysis of an active controller and optimal placement/sizing of distributed piezo actuators based on genetic algorithms for a flexible structure under random disturbance, shows numerical example and the result.

• International Journal of Industrial Entomology and Biomaterials
• /
• 제10권2호
• /
• pp.79-86
• /
• 2005

Molecular markers have increasingly been used in plant genetic analysis, due to their obvious advantages over conventional phenotypic markers, as they are highly polymorphic, more in number, stable across different developmental stages, neutral to selection and least influenced by environmental factors. Among the PCR based marker techniques, ISSR is one of the simplest and widely used techniques, which involves amplification of DNA segment present at an amplifiable distance in between two identical microsatellite repeat regions oriented in opposite direction. Though ISSR markers are dominant like RAPD, they are more stable and reproducible. Because of these properties ISSR markers have recently been found using extensively for finger printing, pohylogenetic analysis, population structure analysis, varietal/line identification, genetic mapping, marker-assisted selection, etc. In mulberry (Morus spp.), ISSR markers were used for analyzing phylogenetic relationship among cultivated varieties, between tropical and temperate mulberry, for solving the vexed problem of identifying taxonomic positions of genotypes, for identifying markers associated with leaf yield attributing characters. As ISSR markers are one of the cheapest and easiest marker systems with high efficiency in generating polymorphism among closely related varieties, they would play a major role in mulberry genome analysis in the future.

• 한국수학사학회지
• /
• 제26권5_6호
• /
• pp.389-400
• /
• 2013

The article makes a discussion to conceptualize a histo-genetic principle in the real historical view point. The classical histo-genetic principle appeared in 19th century was founded by the recapitulation law suggested by biologist Haeckel, but recently it was shown that the theory on it is no longer true. To establish the alternative rationale, several metaphoric characterizations from the history of mathematics are suggested: among them, problem solving, transition of conceptual knowledge to procedural knowledge, generalization, abstraction, circulation from phenomenon to substance, encapsulation to algebraic representation, change of epistemological view, formation of algorithm, conjecture-proof-refutation, swing between theory and application, and so on.

• 대한조선학회논문집
• /
• 제46권1호
• /
• pp.87-95
• /
• 2009

The applicability of optimization techniques for hull surface fitting has been important in the ship design process. In this research, the Genetic Algorithm has been used as a searching technique for solving surface fitting problem and minimizing errors between B-spline surface and the ship's offset data. The encoded design variables are the location of the vertex points and parametric values. The sufficient accuracy in surface fitting implies not only various techniques for computer-aided design, but also the future production design.

• 대한전자공학회:학술대회논문집
• /
• 대한전자공학회 2004년도 ICEIC The International Conference on Electronics Informations and Communications
• /
• pp.400-404
• /
• 2004

There are many methods to find solutions for Integer Programming problems (IPs) such as the Branch-Bound philosophy or the Cutting Plane algorithm. However, most of them have a problem that is the explosion of sets in the computing process. In addition, GA is known as a heuristic search algorithm for solutions of optimization problems. It is started from a random initial guess solution and attempting to find one that is the best under some criteria and conditions. The paper will study an artificial intelligent method to solve IPs by using Genetic Algorithms (GAs). The original solution of this was presented in the papers of Fabricio Olivetti de Francaand and Kimmo Nieminen [2003]. However, both have several limitations which causes could be operations in GAs. The paper proposes a method to upgrade these operations and computational results are also shown to support these upgrades.

• 한국멀티미디어학회논문지
• /
• 제4권1호
• /
• pp.82-90
• /
• 2001

유전자 알고리즘(GA: Genetic Algorithm)은 다양한 영역에서 NP 문제를 해결하는 방법으로 알려져 있다. GA는 긴 연산 시간을 필요하다는 결점 때문에 최근 GA를 하드웨어로 구현하려는 연구가 주목 받아왔다. 본 논문은 GA의 하드웨어 구현을 위한 전용 원칩 컴퓨터를 제안한다. 제안된 전용 원칩 컴퓨터는16 비트 CPU core와 하드웨어 GA로 구성되어 있다. 기존의 하드웨어 GA는 GA의 처리하는데 있어서 메인 컴퓨터에 의존적이었으나 제안된 전용 원칩 컴퓨터는 메인 컴퓨터에 독립적이다. 또한 기존의 하드웨어 GA는 염색체의 길이가 고정되어 있는 데 비해 제안된 전용 원칩 컴퓨터의 염색체의 길이는 가변이며 16 비트 단위로 Pipeline 처리를 한다. 실험 결과는 제안된 원칩 컴퓨터가 랜덤 비트 동기 회로를 위한 진화 하드웨어 설계에 적용할 수 있다는 것을 보여준다.

• IEIE Transactions on Smart Processing and Computing
• /
• 제2권6호
• /
• pp.367-372
• /
• 2013

Cloud computing technology has been developing at an increasing expansion rate. Today most of firms are using this technology, making improving the quality of service one of the most important issues. To achieve this, the system must operate efficiently with less idle time and without deteriorating the customer satisfaction. This paper focuses on enhancing the efficiency of a conventional Genetic Algorithm (GA) for task scheduling in cloud computing using Fuzzy Logic (FL). This study collected a group of task schedules and assessed the quality of each task schedule with the user expectation. The work iterates the best scheduling order genetic operations to make the optimal task schedule. General GA takes considerable time to find the correct scheduling order when all the fitness function parameters are the same. GA is an intuitive approach for solving problems because it covers all possible aspects of the problem. When this approach is combined with fuzzy logic (FL), it behaves like a human brain as a problem solver from an existing database (Memory). The present scheme compares GA with and without FL. Using FL, the proposed system at a 100, 400 and 1000 sample size*5 gave 70%, 57% and 47% better improvement in the task time compared to GA.

• Asia pacific journal of information systems
• /
• 제16권1호
• /
• pp.71-84
• /
• 2006

Case-based reasoning (CBR) is a reasoning technique that reuses past cases to find a solution to the new problem. It often shows significant promise for improving effectiveness of complex and unstructured decision making. It has been applied to various problem-solving areas including manufacturing, finance and marketing for the reason. However, the design of appropriate case indexing and retrieval mechanisms to improve the performance of CBR is still a challenging issue. Most of the previous studies on CBR have focused on the similarity function or optimization of case features and their weights. According to some of the prior research, however, finding the optimal k parameter for the k-nearest neighbor (k-NN) is also crucial for improving the performance of the CBR system. In spite of the fact, there have been few attempts to optimize the number of neighbors, especially using artificial intelligence (AI) techniques. In this study, we introduce a genetic algorithm (GA) to optimize the number of neighbors to combine. This study applies the novel approach to Korean stock market. Experimental results show that the GA-optimized k-NN approach outperforms other AI techniques for stock market prediction.

• Journal of Electrical Engineering and Technology
• /
• 제10권3호
• /
• pp.944-951
• /
• 2015

Pulse Width Modulation (PWM) techniques are increasingly employed for PWM inverter fed induction motor drive. Among various popular PWM methods used, Selective Harmonic Elimination PWM (SHEPWM) has been widely accepted for its better harmonic elimination capability. In addition, using SHEPWM, it is also possible to maintain better voltage regulation. Hence, in this paper, an attempt has been made to apply Bacterial Foraging Algorithm (BFA) for solving selective harmonic elimination problem. The problem of voltage harmonic elimination together with output voltage regulation is drafted as an optimization task and the solution is sought through proposed method. For performance comparison of BFA, the results obtained are compared with other techniques such as derivative based Newton-Raphson method, and Genetic Algorithm. From the comparison, it can be observed that BFA based approach yields better results. Further, it provides superior convergence, reduced computational burden, and guaranteed global optima. The simulation results are validated through experimental findings.

• 한국항해항만학회지
• /
• 제30권2호
• /
• pp.137-143
• /
• 2006

The optimum grillage design belongs to nonlinear constrained optimization problem. The determination of beam scantlings for the grillage structure is a very crucial matter out of whole structural design process. The performance of optimization methods, based on penalty functions, is highly problem-dependent and many methods require additional tuning of some variables. This additional tuning is the influences of penalty coefficient, which depend strongly on the degree of constraint violation. Moreover, Binary-coded Genetic Algorithm (BGA) meets certain difficulties when dealing with continuous and/or discrete search spaces with large dimensions. With the above reasons, Real-coded Micro-Genetic Algorithm ($R{\mu}GA$) is proposed to find the optimum beam scantlings of the grillage structure without handling any of penalty functions. $R{\mu}GA$ can help in avoiding the premature convergence and search for global solution-spaces, because of its wide spread applicability, global perspective and inherent parallelism. Direct stiffness method is used as a numerical tool for the grillage analysis. In optimization study to find minimum weight, sensitivity study is carried out with varying beam configurations. From the simulation results, it has been concluded that the proposed $R{\mu}GA$ is an effective optimization tool for solving continuous and/or discrete nonlinear real-world optimization problems.