• Bulletin of the Korean Mathematical Society
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• v.51 no.1
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• pp.43-54
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• 2014

This paper is concerned with nonlinear evolution differential equations with infinite delay in Banach spaces. Using Kato's approximating approach, existence and uniqueness of strong solutions are obtained.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.317-320
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• 2004

In this work we have managed to find parameters for defining athlete's aerobic and anaerobic thresholds. Thresholds which are of vital importance for top athletes. It is shown how differential evolution and different similarity measures has been used to tune computational model for threshold definitions. From our results it is obvious that the use of right parameter values for this kind expert system is of vital importance.

• East Asian mathematical journal
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• v.30 no.1
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• pp.79-91
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• 2014

We consider the parabolic evolution differential equation such as heat equation and porus-medium equation on a Riemannian manifold M whose Ricci curvature is bounded below by $-(n-1)k^2$ and bounded below by 0 on some amount of M. We derive some bounds of differential quantities for a positive solution and some inequalities which resemble Harnack inequalities.

• Communications of the Korean Mathematical Society
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• v.11 no.4
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• pp.1003-1013
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• 1996

The existence of a bounded generalized solution on the real line for a nonlinear functional evolution problem of the type $$ (FDE) x'(t) + A(t,x_t)x(t) \ni 0, t \in R $$ in a general Banach spaces is considered. It is shown that (FDE) has a bounded generalized solution on the whole real line with well-known Crandall and Pazy's result and recent results of the functional differential equations involving the operator A(t).

• Journal of the Korean Mathematical Society
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• v.50 no.1
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• pp.41-59
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• 2013

In this paper, we investigate the existence and controllability results for a class of abstract stochastic evolution differential inclusions with nonlocal conditions where the linear part is nondensely defined and satisfies the Hille-Yosida condition. The results are obtained by using integrated semigroup theory and a fixed point theorem for condensing map due to Martelli.

• Proceedings of the Korean Society of Computer Information Conference
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• 2022.01a
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• pp.391-392
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• 2022

본 논문에서는 SparkHDE-EM이라는 생태학적 모델 알고리즘에 기반한 하이브리드 DE를 제안한다. 그리고 Spark 기반 아일랜드 모델을 도입하여 다양한 DE 변종의 병렬화를 구현한다. 또한 Monod 모델을 활용하여 자원 간의 균형을 유지하는 방법을 제안한다.

• Smart Structures and Systems
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• v.26 no.3
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• pp.345-360
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• 2020

Modern swarm intelligence heuristic search methods are widely applied in the field of structural health monitoring due to their advantages of excellent global search capacity, loose requirement of initial guess and ease of computational implementation etc. To this end, a hybrid strategy is proposed based on butterfly optimization algorithm (BOA) and differential evolution (DE) with purpose of effective combination of their merits. In the proposed identification strategy, two improvements including mutation and crossover operations of DE, and dynamic adaptive operators are introduced into original BOA to reduce the risk to be trapped in local optimum and increase global search capability. The performance of the proposed algorithm, hybrid butterfly optimization and differential evolution algorithm (HBODEA) is evaluated by two numerical examples of a simply supported beam and a 37-bar truss structure, as well as an experimental test of 8-story shear-type steel frame structure in the laboratory. Compared with BOA and DE, the numerical and experimental results show that the proposed HBODEA is more robust to detect the reduction of stiffness with limited sensors and contaminated measurements. In addition, the effect of search space, two dynamic operators, population size on identification accuracy and efficiency of the proposed identification strategy are further investigated.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.13 no.1
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• pp.39-49
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• 2013

This paper presents a method of improving the performance of a day-ahead 24-h load curve and peak load forecasting. The next-day load curve is forecasted using radial basis function (RBF) neural network models built using the best design parameters. To improve the forecasting accuracy, the load curve forecasted using the RBF network models is corrected by the weighted sum of both the error of the current prediction and the change in the errors between the current and the previous prediction. The optimal weights (called "gains" in the error correction) are identified by differential evolution. The peak load forecasted by the RBF network models is also corrected by combining the load curve outputs of the RBF models by linear addition with 24 coefficients. The optimal coefficients for reducing both the forecasting mean absolute percent error (MAPE) and the sum of errors are also identified using differential evolution. The proposed models are trained and tested using four years of hourly load data obtained from the Korea Power Exchange. Simulation results reveal satisfactory forecasts: 1.230% MAPE for daily peak load and 1.128% MAPE for daily load curve.

• Journal of Electrical Engineering and Technology
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• v.10 no.4
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• pp.1508-1517
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• 2015

Optimal Power dispatch is the short-term decision of the optimal output of a number of power generation facilities, to meet the system demand, with the objective of Power dispatching at the lowest possible cost, subject to transmission lines power loss and operational constraints. The operational constraint includes power balance constraint, generator limit constraint, and emission dispatch constraint and valve point effects. In this paper, Opposition based Differential Evolution Algorithm (ODEA) has been proposed to handle the objective function and the operational constraints simultaneously. Furthermore, the valve point loading effects and transmission lines power loss are also considered for the efficient and effective Power dispatch. The ODEA has unique features such as self tuning of its control parameters, self acceleration and migration for searching. As a result, it requires very minimum executions compared with other searching strategies. The effectiveness of the algorithm has been validated through four standard test cases and compared with previous studies. The proposed method out performs the previous methods.

• Journal of Electrical Engineering and Technology
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• v.13 no.6
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• pp.2301-2309
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• 2018

In a field-oriented vector-controlled permanent magnet synchronous motor (PMSM) control system, the d-axis current control loop can offer a free degree of freedom which can be used to improve control performances. However, in the industry the desired d-axis current command is usually set as zero without using the free degree of freedom. This paper proposes a method to use the degree of freedom for control performance improvement. It is assumed that both the inner loop proportional-integral (PI) current controller and the q-axis outer loop PI speed controller are tuned by the well-known tuning rules. This paper gives an optimal d-axis reference current command generator such that some useful performance indexes are minimized and/or a tradeoff between conflicting performance criteria is made. This paper uses a differential evolution algorithm to autotune the parameter values of the optimal d-axis reference current command generator. This paper implements the proposed control system in real time on a Texas Instruments TMS320F28335 floating-point DSP. This paper also gives experimental results showing the practicality and feasibility of the proposed control system, along with simulation results.