• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2002.05a
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• pp.466-468
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• 2002

This paper proposes a new type of evolvable hardware for implementing the clone of Moore State machine. The proposed Evolvable Hardware is employed efficient pipeline parallelization, handshaking mechanism and fitness function in FPGA Genetic Algorithm(GA) has known as a method of solving NP problem in various applications. Since a major drawback of the GA is that it needs a long computation time, the hardware implementation of Genetic Algorithm is focused on in recent studies. Conventional hardware GA uses the fired length of chromosome but the proposed Evolvable Hardware uses the variable length of chromosome by the efficient 16 bit Pipeline Unit. Experimental results show that the proposed evolvable hardware is applicable to the implementation of the clone for Moore State machine

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.1
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• pp.98-103
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• 2000

This paper suggests a method to recognize the various defect patterns of a cold mill strip using a binary decision tree automatically constructed by a genetic algorithm(GA). In classifying complex patterns with high similarity like the defect patterns of a cold mill stirp, the selection of an optimal feature set and an appropriate recognizer is important to achieve high recognition rate. In this paper a GA is used to select a subset of the suitable features at each node in the binary decision tree. The feature subset with maximum fitness is chosen and the patterns are classified into two classes using a linear decision function. This process is repeated at each node until all the patterns are classified into individual classes. In this way, the classifier using the binary decision tree is constructed automatically. After constructing the binary decision tree, the final recognizer is accomplished by having neural network learning sits of standard patterns at each node. In this paper, the classifier using the binary decision tree is applied to the recognition of defect patterns of a cold mill strip, and the experimental results are given to demonstrate the usefulness of the proposed scheme.

• 전자공학회논문지 IE
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• v.45 no.4
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• pp.27-32
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• 2008

This paper presents the implementation of simple genetic algorithm using hardware description language for evolvable hardware embedded system. Evolvable hardware refers to hardware that can change its architecture and behavior dynamically and autonomously by interacting with its environment. So, it is especially suited to applications where no hardware specifications can be given in advance. Evolvable hardware is based on the idea of combining reconfigurable hardware device with evolutionary computation, such as genetic algorithm. Because of parallel, no function call overhead and pipelining, a hardware genetic algorithm give speedup over a software genetic algorithm. This paper suggests the hardware genetic algorithm for evolvable embedded system chip. That includes simulation results for several fitness functions.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.21 no.46
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• pp.33-49
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• 1998

In order to improve the performance of relational databases, one has to reduce the number of disk accesses necessary to transfer data from disk to main memory. The paper proposes to reduce the number of disk I/O accesses by vertically partitioning relation into fragments and allowing attribute replication to fragments if necessary. When zero-one integer programming model is solved by the branch-and-bound method, it requires much computing time to solve a large sized problem. Therefore, heuristic solutions using genetic algorithm(GA) are presented. GA in this paper adapts a few ideas which are different from traditional genetic algorithms, for examples, a rank-based sharing fitness function, elitism and so on. In order to improve performance of GA, a set of optimal parameter levels is determined by the experiment and makes use of it. As relations are vertically partitioned allowing attribute replications and saved in disk, an attribute replicating vertical partition method by GA can attain less access cost than non-attribute-replication one and require less computing time than the branch-and-bound method in large-sized problems. Also, it can acquire a good solution similar to the optimum solution in small-sized problem.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.8
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• pp.135-143
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• 2003

This paper presents the impact minimization of a biped robot by using genetic algorithm. In case we want to accomplish the designed plan under the special environments, a robot will be required to have walking capability and patterns with legs, which are in a similar manner as the gaits of insects, dogs and human beings. In order to walk more effectively, studies of mobile robot movement are needed. To generate optimal motion for a biped robot, we employ genetic algorithm. Genetic algorithm is searching for technology that can look for solution from the whole district, and it is possible to search optimal solution from a fitness function that needs not to solve differential equation. In this paper, we generate trajectories of gait and trunk motion by using genetic algorithm. Using genetic algorithm not only on gait trajectory but also on trunk motion trajectory, we can obtain the smoothly stable motion of robot that has the least impact during the walk. All of the suggested motions of biped robot are investigated by simulations and verified through the real implementation.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.4
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• pp.388-394
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• 1999

This paper is concerned with an application of Parallel Genetic Algorithms(PGA) to optimal econmic load dispatch(ELD) in power systems. The ELD problem is to minimize the total generation fuel cost of power outputs for all generating units while satisfying load balancing constraints. Genetic Algorithms(GA) is a good candidate for effective parallelization because of their inherent principle of evolving in parallel a population of individuals. Each individual of a population evaluates the fitness function without data exchanges between individuals. In application of the parallel processing to GA, it is possible to use Single Instruction stream, Multiple Data stream(SIMD), a kind of parallel system. The architecture of SIMD system need not data communications between processors assigned. The proposed ELD problem with C code is implemented by SIMSCRIPT language for parallel processing which is a powerfrul, free-from and versatile computer simulation programming language. The proposed algorithms has been tested for 38 units system and has been compared with Sequential Quadratic programming(SQP).

• The Journal of the Korea institute of electronic communication sciences
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• v.8 no.11
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• pp.1665-1674
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• 2013

In this paper, we propose a genetic algorithm(GA) based locomotion method of a quadruped robot with waist joint, which makes a quadruped robot walk on the slop efficiently. In the proposed method, we first derive the kinematic model of a quadruped robot with waist joint and then set the gene and the fitness function for GA. In addition, we determine the best attitude for a quadruped robot and the landing point of a foot in the walk space, which has the optimal energy stability margin(ESM). Finally, we verify the effectiveness of the proposed method by comparing with the performance of the previous method through the computer simulations.

• Journal of Electrical Engineering and Technology
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• v.13 no.3
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• pp.1079-1088
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• 2018

A line overload emergency control strategy based on the source-load synergy coefficient is proposed in this paper. First, the definition of the source-load synergy coefficient is introduced. When line overload is detected, the source-load branch synergy coefficient and source-load distribution synergy coefficient are calculated according to the real-time operation mode of the system. Second, the generator tripping and load shedding control node set is determined according to the source-load branch synergy coefficient. And then, according to the line overload condition, the control quantity of each control node is determined using the Double Fitness Particle Swarm Optimization (DFPSO), with minimum system economic loss as the objective function. Thus load shedding for the overloaded line could be realized. On this basis, in order to guarantee continuous and reliable power supply, on the condition that no new line overload is caused, some of the untripped generators are selected according to the source-load distribution synergy coefficient to increase power output. Thus power supply could be restored to some of the shedded loads, and the economic loss caused by emergency control could be minimized. Simulation tests on the IEEE 10-machine 39-bus system verify the effectiveness and feasibility of the proposed strategy.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.6 no.5
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• pp.718-723
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• 2002

This paper proposes a new type of evolvable hardware for implementing the clone of Moore State machine. The proposed Evolvable Hardware is employed efficient pipeline parallelization, handshaking mechanism and fitness function in FPGA. Genetic Algorithm(GA) has known as a method of solving NP problem in various applications. Since a major drawback of the GA is that it needs a long computation time, the hardware implementation of Genetic Algorithm is focused on in recent studies. Conventional hardware GA uses the fixed length of chromosome but the proposed Evolvable Hardware uses the variable length of chromosome by the efficient 16 bit Pipeline Unit. Experimental results show that the proposed evolvable hardware is applicable to the implementation of the clone for Moore State machine.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.10a
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• pp.808-813
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• 2005

Structural integrity assessment of defected pipe is important in fitness for service evaluation and proper engineering assessment is needed to determine whether pipelines are still fit for service. This paper present a failure prediction of gas pipes made of APIl X65 steel with gouge using stress-modified true fracture strain, which is regarded as a criterion of ductile fracture. For this purpose, API X65 pipes with gouge are simulated using elastic-plastic FE analyses with the proposed ductile failure criterion and the resulting burst pressures are compared with experimental data. Agreements are quite good, which gives confidence in the use of the proposed criteria to defect assessment fer gas pipelines. Then, further extensive finite element analyses are performed to obtain the burst pressure solution of pipes with gouge as a function of defect depth, length and pipeline geometry.