• 대한가정학회지
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• 제48권5호
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• pp.61-72
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• 2010

This study examined the effects of maternal parenting, children's self-esteem and emotion regulation strategy on emotion regulation. Data were collected from 493 5th and 6th graders. The results were as follows: Firstly, maternal authoritarian and permissive parenting directly affected children's maladaptive emotion regulation, while maternal affectionate and permissive parenting directly affected children's adaptive emotion regulation. Secondly, children's selfesteem directly affected both their maladaptive and adaptive emotion regulation, while also acting as a mediator between maternal parenting and children's maladaptive and adaptive emotion regulation. Children's cognitive reappraiser strategy positively affected adaptive emotion regulation, but emotion suppressive strategy negatively affected adaptive emotion regulation. These emotion regulation strategies played a mediating role between maternal parenting or children's self-esteem and adaptive emotion regulation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권9호
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• pp.2976-2990
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• 2022

The adaptive adjustment of reference or weight vectors in decomposition-based methods has been a hot research topic in the evolutionary community over the past few years. Although various methods have been proposed regarding this issue, most of them aim to diversify solutions in the objective space to cover the true Pareto fronts as much as possible. Different from them, this paper proposes a knee point-based reference vector adaptive adjustment strategy to concurrently balance the convergence and diversity. To be specific, the knee point-based reference vector adaptive adjustment strategy firstly utilizes knee points to construct the adaptive reference vectors. After that, a new fitness function is defined mathematically. Then, this paper further designs a many-objective evolutionary algorithm with knee point-based reference vector adaptive adjustment strategy, where the mating operation and environmental selection are designed accordingly. The proposed method is extensively tested on the WFG test suite with 8, 10 and 12 objectives and MPDMP with state-of-the-art optimizers. Extensive experimental results demonstrate the superiority of the proposed method over state-of-the-art optimizers and the practicability of the proposed method in tackling practical many-objective optimization problems.

• Journal of Power Electronics
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• 제19권2호
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• pp.549-559
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• 2019

This paper proposes an adaptive sliding mode control (ASMC) strategy with an enhanced optimal reaching law (EORL) for the robust current tracking control of the boost converter based hybrid power source (HPS) in an electric vehicle (EV). A conventional ASMC strategy based on state observers and the hysteresis control method is used to realize the current tracking control for the boost converter based HPS. Then a novel enhanced exponential reaching law is proposed to improve the ASMC. Moreover, an enhanced exponential reaching law is optimized by particle swarm optimization. Finally, the adaptive control factor is redesigned based on the EORL. Simulations and experiments are established to validate the ASMC strategy with the EORL. Results show that the ASMC strategy with the EORL has an excellent current tracking control effect for the boost converter based HPS. When compared with the conventional ASMC strategy, the convergence time of the ASMC strategy with the EORL can be effectively improved. In EV applications, the ASMC strategy with the EORL can achieve robust current tracking control of the boost converter based HPS. It can guarantee the active and stable power distribution for boost converter based HPS.

• 인터넷정보학회논문지
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• 제22권1호
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• pp.1-11
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• 2021

Estimation of distribution algorithm (EDA) is a popular stochastic metaheuristic algorithm. EDA has been widely utilized in various optimization problems. However, it has been shown that the diversity of the population gradually decreases during the iterations, which makes EDA easily lead to premature convergence. This article introduces a hybrid estimation of distribution algorithm (EDA) with differential evolution (DE) based on self-adaptive strategy, namely HEDADE-SA. Firstly, an alternative probability model is used in sampling to improve population diversity. Secondly, the proposed algorithm is combined with DE, and a self-adaptive strategy is adopted to improve the convergence speed of the algorithm. Finally, twenty-five benchmark problems are conducted to verify the performance of HEDADE-SA. Experimental results indicate that HEDADE-SA is a feasible and effective algorithm.

• Structural Engineering and Mechanics
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• 제74권4호
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• pp.547-557
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• 2020

In this paper, an automatic adaptive mesh refinement procedure is presented for two-dimensional problems on the basis of a new probabilistic error estimator. First-order perturbation theory is employed to determine the lower and upper bounds of the structural displacements and stresses considering uncertainties in geometric sizes, material properties and loading conditions. A new probabilistic error estimator is proposed to reduce the mesh dependency of the responses dispersion. The suggested error estimator neglects the refinement at the critical points with stress concentration. Therefore, the proposed strategy is combined with the classic adaptive mesh refinement to achieve an optimal mesh refined properly in regions with either high gradients or high dispersion of the responses. Several numerical examples are illustrated to demonstrate the efficiency, accuracy and robustness of the proposed computational algorithm and the results are compared with the classic adaptive mesh refinement strategy described in the literature.

• 한국시뮬레이션학회:학술대회논문집
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• 한국시뮬레이션학회 2001년도 The Seoul International Simulation Conference
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• pp.37-43
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• 2001

New product development has been a key element fur organizational evolution. The bulk of research about new product strategy has focused solely on new product development function itself. This paper investigates cross-functional elements in new product development. More specifically, we suggest that there must exist a fit between new product strategy and value chain strategy. It means that, in order to support new product development activity, there must exist a relevant value chain strategy. We consider three types of integration - internal integration, customer integration, and supplier integration - as strategic elements of value chain strategy. For the case of new product strategy, we consider market newness and product technology unfamiliarity as strategic elements. We also consider two types of learning characteristic, i.e., \\\"fast-adaptive learning\\\" and \\\"slow-adaptive leaning\\\" as control factor. Learning characteristic represents firms organizational capability related with organizational learning. For example, fur fast-adaptive learning case, the effect of integration appears early in time. System dynamics simulation is employed to verify our research framework. The results exhibit that there must exist cross-functional relationships between value chain strategy and new product strategy in order to shorten total development time.al development time.

• Journal of Electrical Engineering and Technology
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• 제9권4호
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• pp.1182-1187
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• 2014

This paper proposes an energy management strategy and adaptive control for superconducting magnetic energy storage (SMES) in a distribution power system with a grid-connected photovoltaic (PV) farm. Application of the SMES system can decrease the output power fluctuations of PV system effectively. Also, it can control the real and reactive powers corresponding to the scheduled reference values with adequate converter capacity, which are required at a steady-state operating point. Therefore, the adaptive control strategy for SMES plays a key role in improving the system stability when the PV generation causes uncertain variations due to weather conditions. The performance of proposed energy management strategy and control method for the SMES is then evaluated with several case studies based on the PSCAD/EMTDC$^{(R)}$ simulation.

• 정보처리학회논문지:소프트웨어 및 데이터공학
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• 제4권3호
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• pp.111-120
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• 2015

최근 동적인 환경에서 발생하는 다양한 문제를 스스로 해결할 수 있는 자가 적응 시스템에 대한 연구가 활발히 이루어지고 있다. 자가 적응 시스템에서 시스템이 문제를 스스로 인식하고 자가 적응할 수 있도록 요구사항을 설계하는 과정은 필수적이며, 만약 기존의 적응 전략들을 재사용하여 자가 적응 시스템을 설계한다면 소요되는 시간 및 비용을 절감할 수 있다. 따라서 이 논문은 새로운 자가 적응 시스템 개발 시 기존의 자가 적응 시스템으로부터 재사용 가능한 적응 전략을 추출하는 시스템을 제안한다. 이를 위하여 자가 적응 요소를 지식화하여 적응 전략 온톨로지 및 타깃 시스템 온톨로지를 정의하고, 이러한 온톨로지를 기반으로 재사용 가능한 적응 전략을 추출하는 기법을 기술한다. 또한, 이 논문은 제안 시스템을 구현하고 추출된 적응 전략에 대한 재사용률을 측정함으로써 제안 시스템을 비교 평가한다. 평가 결과, 제안 시스템은 추출된 적응 전략이 정확히 동작함을 보이며 제안 시스템의 추출 기법은 기존의 재사용 기법보다 높은 재사용률을 보인다.

• Structural Engineering and Mechanics
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• 제54권2호
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• pp.239-256
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• 2015

An adaptive-scale damage detection strategy based on a wavelet finite element model (WFEM) for thin plate structures is established in this study. Equations of motion and corresponding lifting schemes for thin plate structures are derived with the tensor products of cubic Hermite multi-wavelets as the elemental interpolation functions. Sub-element damages are localized by using of the change ratio of modal strain energy. Subsequently, such damages are adaptively quantified by a damage quantification equation deduced from differential equations of plate structure motion. WFEM scales vary spatially and change dynamically according to actual needs. Numerical examples clearly demonstrate that the proposed strategy can progressively locate and quantify plate damages. The strategy can operate efficiently in terms of the degrees-of-freedom in WFEM and sensors in the vibration test.

• 한국정보과학회논문지:소프트웨어및응용
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• 제32권11호
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• pp.1099-1110
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• 2005

전자상거래상에서 경매가 활발해짐에 따라 경매용 에이전트와 경매 에이전트의 비딩 스트레티지 개발에 관한 연구가 중요한 관심의 초점이 되고 있다. 특히, 우세한 스트레티지가 알려져 있지 않는 복잡한 경매 환경에서의 에이전트 스트레티지 개발은 실용적인 의미를 가지고 있다 이 논문은 최적의 스트레티지가 존재하지 않는 연속이중경매(Continuous Double Auction, CDA) 환경에서 사용할 수 있는 "적응성 스트레티지"를 소개한다. 적응성 스트레티지는 현재 알려져 있는 P-스트레티지에 실시간 적응력을 부가하는 것을 주 아이디어로 한다. 적응성 스트레티지는 여러 종류의 알려진 스트레티지들 중 이제까지 좋은 성능을 보여준 스트레티지를 계속 사용하려는 탐색(exploitation)과 바뀌어졌을지도 모르는 새로운 환경에 적합한 스트레티지를 찾아내려는 이용(exploration)간의 균형을 꾀하며, 이를 각 스트레티지의 기대이득과 실행횟수사이의 상반관계를 고려하는 휴리스틱 탐색 함수를 이용하여 결정한다. 실험분석의 결과, 적응성 스트레티지는 (1) P-스트레티지가 잘 작동하지 않는 환경에선 P-스트레티지보다 높은 이득을, (2) P-스트레티지가 다른 종류의 단순한 스트레티지를 앞서는 환경에서는 P-스트레티지와 비슷한 이득을 보인다.