• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.5
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• pp.712-717
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• 2008

In swarm robot systems, each robot must act by itself according to the its states and environments, and if necessary, must cooperate with other robots in order to carry out a given task. Therefore it is essential that each robot has both learning and evolution ability to adapt the dynamic environments. In this paper, reinforcement learning method with SVM based on structural risk minimization and distributed genetic algorithms is proposed for behavior learning and evolution of collective autonomous mobile robots. By distributed genetic algorithm exchanging the chromosome acquired under different environments by communication each robot can improve its behavior ability. Specially, in order to improve the performance of evolution, selective crossover using the characteristic of reinforcement learning that basis of SVM is adopted in this paper.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.2
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• pp.279-284
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• 2009

In swarm robot systems, each robot must behaves by itself according to the its states and environments, and if necessary, must cooperates with other robots in order to carry out a given task. Therefore it is essential that each robot has both learning and evolution ability to adapt the dynamic environments. In this paper, reinforcement learning method using many SVM based on structural risk minimization and distributed genetic algorithms is proposed for behavior learning and evolution of collective autonomous mobile robots. By distributed genetic algorithm exchanging the chromosome acquired under different environments by communication each robot can improve its behavior ability. Specially, in order to improve the performance of evolution, selective crossover using the characteristic of reinforcement learning that basis of Cascade SVM is adopted in this paper.

• ETRI Journal
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• v.30 no.6
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• pp.799-806
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• 2008

In this paper, a new design for an error correcting code (ECC) is proposed. The design is aimed to build an ECC circuitry with minimal power consumption. The genetic algorithm equipped with the symbiotic mechanism is used to design a power-efficient ECC which provides single-error correction and double-error detection (SEC-DED). We formulate the selection of the parity check matrix into a collection of individual and specialized optimization problems and propose a symbiotic evolution method to search for an ECC with minimal power consumption. Finally, we conduct simulations to demonstrate the effectiveness of the proposed method.

• Proceedings of the KIEE Conference
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• 1992.07b
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• pp.577-579
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• 1992

A new algorithm, which combines the Evolution Strategy and the Simplex method, is proposed for the detection of magnetic body utilizing the disturbance of magnetic fields. Although the detection problem of magnetic body which belongs to the inverse problem may have many local minima, the global optimum point was found by introducing the Evolution Strategy. And the convergency rate was enhanced by introducing the Simplex method. Through the numerical examples, the applicability and usefulness of the proposed algorithm are proved.

• Structural Monitoring and Maintenance
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• v.1 no.4
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• pp.427-449
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• 2014

A hybrid optimization method for the identification of state-space models is presented in this study. Hybridization is succeeded by combining the advantages of deterministic and stochastic algorithms in a superior scheme that promises faster convergence rate and reliability in the search for the global optimum. The proposed hybrid algorithm is developed by replacing the original stochastic mutation operator of Evolution Strategies (ES) by the Levenberg-Marquardt (LM) quasi-Newton algorithm. This substitution results in a scheme where the entire population cloud is involved in the search for the global optimum, while single individuals are involved in the local search, undertaken by the LM method. The novel hybrid identification framework is assessed through the Monte Carlo analysis of a simulated system and an experimental case study on a shear frame structure. Comparisons to subspace identification, as well as to conventional, self-adaptive ES provide significant indication of superior performance.

• Proceedings of the KIEE Conference
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• 1997.11a
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• pp.531-533
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• 1997

PI(proportional-integral) controller has been extensively used in the industrial field. But in practicle case, it is difficult to tune PI gains. Evolution Strategy(ES) is used as an effective search algorithm in optimization programs. In this paper we proposed a PI controller for Spot welder system using ES with varying search space. ES with varying search space which depends on fitness values at each generation is used to tune PI control parameters. Simulation results show the proposed algorithm has accurate and robust performance with effective search ability.

• Proceedings of the KIEE Conference
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• 1997.07c
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• pp.781-783
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• 1997

Genetic Algorithm is a kind of an evolution programming based on natural evolution principle. It applied to probabilistic searching, machine learning and optimization, and many good results were reported. Generator maintenance scheduling is an optimization Problem with constraints. This paper applied a genetic algorithm to generator maintenance scheduling problem and tested on sample systems. The results are compared with heuristic method and branch-and-bound method.

• Nuclear Engineering and Technology
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• v.32 no.2
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• pp.169-179
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• 2000

A detailed numerical analysis of the evolution of thermal stratification in a curved piping system in a nuclear power plant is performed. A finite volume based thermal-hydraulic computer code has been developed employing a body-fitted, non-orthogonal curvilinear coordinate for this purpose. The cell-centered, non-staggered grid arrangement is adopted and the resulting checkerboard pressure oscillation is prevented by the application of momentum interpolation method. The SIMPLE algorithm is employed for the pressure and velocity coupling, and the convection terms are approximated by a higher-order bounded scheme. The thermal-hydraulic computer code developed in the present study has been applied to the analysis of thermal stratification in a curved duct and some of the predicted results are compared with the available experimental data. It is shown that the predicted results agree fairly well with the experimental measurements and the transient formation of thermal stratification in a curved duct is also well predicted.

• International Journal of Computer Science & Network Security
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• v.23 no.7
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• pp.16-22
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• 2023

Enhanced radio access technologies (RAT) are deployed in Next Generation Convergence Networks by the service providers so as to satisfy the basic requirements of end-users for e.g. QoS. Whenever the available resources are being shared simultaneously and dynamically by multiple users or distribution of allocated channels randomly, the deficiency of spectral resources and dynamic behavior of Network traffic in real time Networking, we may have problem. In order to evaluate the performance of our proposed algorithm, computer simulation has been performed on NS-2 simulator and a comparison with the existing algorithms has been made.

• ETRI Journal
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• v.45 no.6
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• pp.939-951
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• 2023

It is critical to estimate the location using only Long-Term Evolution (LTE) and Wi-Fi information gathered by the user's smartphone and deployable for emergency rescue, regardless of whether the Global Positioning System is received. In this research, we used a vehicle to gather LTE and Wi-Fi wireless signals over a large area for an extended period of time. After that, we used the learning technique to create a positioning database that included both collection and noncollection points. We presented a two-step positioning algorithm that utilizes coarse localization to discover a rough location in a wide area rapidly and fine localization to estimate a particular location based on the coarse position. We confirmed our technology utilizing different sorts of devices in four regional types that are generally encountered: dense urban, urban, suburban, and rural. Results presented that our algorithm can satisfactorily achieve the target accuracy necessary in emergency rescue circumstances.