• Structural Engineering and Mechanics
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• 제65권4호
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• pp.415-422
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• 2018

The Conjugate Finite-Step Length" (CFSL) algorithm is proposed to improve the efficiency and robustness of first order reliability method (FORM) for reliability analysis of highly nonlinear problems. The conjugate FORM-based CFSL is formulated using the adaptive conjugate search direction based on the finite-step size with simple adjusting condition, gradient vector of performance function and previous iterative results including the conjugate gradient vector and converged point. The efficiency and robustness of the CFSL algorithm are compared through several nonlinear mathematical and structural/mechanical examples with the HL-RF and "Finite-Step-Length" (FSL) algorithms. Numerical results illustrated that the CFSL algorithm performs better than the HL-RF for both robust and efficient results while the CFLS is as robust as the FSL for structural reliability analysis but is more efficient.

• Advances in robotics research
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• 제2권1호
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• pp.1-11
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• 2018

To monitor the environment and determine the source of a pollutant gradient using a multiple robot swarm, we propose a hybrid algorithm that combines two bio-inspired algorithms mimicking chemotaxis and pheromones of bacteria. The algorithm is implemented in virtual robot agents in a simulator to evaluate their feasibility and efficiency in gradient maps with different sizes. Simulation results show that the chemotaxis controller guided robot agents to the locations with higher pollutant concentrations, while the pheromone marked in a virtual field increased the efficiency of the search by reducing the visiting redundancy. The number of steps required to reach the target point did not increase proportionally as the map size increased, but were less than those in the linear whole-map search method. Furthermore, the robot agents could function with simple sensor composition, minimum information about the map, and low calculation capacity.

• Journal of applied mathematics & informatics
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• 제29권1_2호
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• pp.173-190
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• 2011

In this paper, we construct a new approach of affine scaling interior algorithm using the affine scaling conjugate gradient and Lanczos methods for bound constrained nonlinear optimization. We get the iterative direction by solving quadratic model via affine scaling conjugate gradient and Lanczos methods. By using the line search backtracking technique, we will find an acceptable trial step length along this direction which makes the iterate point strictly feasible and the objective function nonmonotonically decreasing. Global convergence and local superlinear convergence rate of the proposed algorithm are established under some reasonable conditions. Finally, we present some numerical results to illustrate the effectiveness of the proposed algorithm.

• Water Engineering Research
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• 제1권1호
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• pp.63-74
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• 2000

This paper presents a two- phase search scheme for optimal pipe expansion of expansion of existing water distribution systems. In pipe network problems, link flows affect the total cost of the system because the link flows are not uniquely determined for various pipe diameters. The two-phase search scheme based on stochastic optimization scheme is suggested to determine the optimal link flows which make the optimal design of existing pipe network. A sample pipe network is employed to test the proposed method. Once the best tree network is obtained, the link flows are perturbed to find a near global optimum over the whole feasible region. It should be noted that in the perturbation stage the loop flows obtained form the sample existing network are employed as the initial loop flows of the proposed method. It has been also found that the relationship of cost-hydraulic gradient for pipe expansion of existing network affects the total cost of the sample network. The results show that the proposed method can yield a lower cost design than the conventional design method and that the proposed method can be efficiently used to design the pipe expansion of existing water distribution systems.

• 인지과학
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• 제4권2호
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• pp.181-200
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• 1994

다층 신경망의 학습에 있어서 역전파 알고리즘은 시스템이 지역적 최소치에 빠질수 있고,탐색공간의 피라미터들에 의해 신경망 시스템의 성능이 크게 좌우된다는 단점이 있다.이러한 단점을 보완하기 의해 유전자 알고리즘이 신경망의 학습에 도입도었다.그러나 유전자 알고리즘에는 역전파 알고리즘과 같은 미세 조정되는 지역적 탐색(fine-tuned local search) 을 위한 메카니즘이 존재하지 않으므로 시스템이 전역적 최적해로 수렴하는데 많은 시간을 필요로 한다는 단점이 있다. 따라서 본 논문에서는 역전파 알고리즘의 기울기 강하 기법(gradient descent method)을 교배나 돌연변이와 같은 유전 연산자로 둠으로써 유전자 알고리즘에 지역적 미세 조정(local fine-tuning)을 위한 메카니즘을 제공해주는 새로운 형태의 GA-BP 방법을 제안한다.제안된 방법의 유용성을 보이기 위해 3-패러티 비트(3-parity bit) 문제에 실험하였다.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2010년도 추계학술대회 논문집
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• pp.317-318
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• 2010

• Journal of Advanced Marine Engineering and Technology
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• 제25권5호
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• pp.1115-1121
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• 2001

This paper presents the development of a tracking algorithm for shipborad satellite antenna systems which can enhance the tracking performance. In order to overcome some drawbacks of the conventional step tracking algorithm a new tracking algorithm is proposed. The proposed algorithm searches for the best tracking angles using gradient-based formulae and signal intensities measured according to a search pattern. The effectiveness of the proposed algorithm is demonstrated through simulation using real data.

• 한국항해학회지
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• 제25권4호
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• pp.361-369
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• 2001

This thesis describes the design of a stabilized algorithm for shipboard satellite antenna systems which can enhance the tracking performance. In order to overcome some drawbacks of the conventional step tracking algorithm, the proposed algorithm searches for the best tracking angles using gradient-based formulae and signal intensities measured according to a search pattern. The effectiveness of the proposed algorithm is demonstrated through simulation using real-world data.

• 한국마린엔지니어링학회:학술대회논문집
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• 한국마린엔지니어링학회 2001년도 춘계학술대회 논문집
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• pp.219-224
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• 2001

This paper presents the development of a tracking algorithm for shipboard satellite antenna systems which can enhance the tracking performance. In order to overcome some drawbacks of the conventional step tracking algorithm, the proposed algorithm searches for the best tracking angles using gradient-based formulae and signal intensities measured according to a search pattern. The effectiveness of the proposed algorithm is demonstrated through simulation using real-world data.

• 센서학회지
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• 제26권4호
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• pp.251-258
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• 2017

According to recent studies by scientists about how to search for food, homes and the mates, it is found that the gradient information plays a key role. From cells to insects and large animals, they mostly either have special sensing organism or use a strategy to measure the gradient. Use of a perturbation as an additional input is introduced for sensor signal processing in order to get the gradient information. Different from typical approach, which calculates the gradient from differentiation, the proposed processing is done by a form of integration, thus it is very robust to noise. Discrete time domain analyses are given for one, two and three input functions for the estimation of the gradients. The amplitude and the frequency of the perturbation are two important parameters for this approach. A quantitative index to measure the effects of the amplitude is developed based on the linear regression analysis. The frequency of the perturbation is to be selected high enough to finish one period of the perturbation before the property is changed significantly with respect to time. Another quantitative index is proposed for guiding the selection of the frequency.