http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
- 中文 을 입력하시려면 zhongwen을 입력하시고 space를누르시면됩니다.
- 北京 을 입력하시려면 beijing을 입력하시고 space를 누르시면 됩니다.
RISS 인기검색어
- 검색키워드
- 저자 : Zhou Huiling (검색결과 4 건)
- 무료
- 기관 내 무료
- 유료
-
Effect of Laser Power on Hybrid Laser-Gas Metal Arc Welding (GMAW) of a 6061 Aluminum Alloy
Zhou Huiling,Fu Fanglian,Dai Zhixin,Qiao Yanxin,Chen Jian,Yang Lanlan,Liu Wen 한국물리학회 2020 THE JOURNAL OF THE KOREAN PHYSICAL SOCIETY Vol.77 No.11
The effect of laser power on the geometrical characteristics, microstructure and micro-hardness of the welding joints for 6061 aluminum alloy after hybrid laser-gas metal arc welding (GMAW) was investigated. The results showed that the welding joints from "Bottom" to "Top" were mainly composed of planar crystals, columnar crystals, and equiaxed dendrites. With increasing laser power, the weld depth and width and the grain size increased. When the laser power reached 5 kW, pores could be found in the weld pool region. Micro-hardness measurements showed that the application of higher laser power hardly changed the hardness of the welding joint.
-
Advanced orthogonal learning and Gaussian barebone hunger games for engineering design
Zhou Xinsen,Gui Wenyong,Heidari Ali Asghar,Cai Zhennao,Elmannai Hela,Hamdi Monia,Liang Guoxi,Chen Huiling 한국CDE학회 2022 Journal of computational design and engineering Vol.9 No.5
The hunger games search (HGS) algorithm is a recently proposed population-based optimization algorithm that mimics a common phenomenon of animals searching for food due to hunger stimuli and has a simple and easy-to- understand structure. However, the original HGS still suffers from shortcomings, such as low population diversity and the tendency to fall into local optima. To remedy these shortcomings, an improved HGS, called OCBHGS, is proposed, which introduces three main strategies, namely the chaotic initialization strategy, the Gaussian barebone mechanism, and the orthogonal learning strategy. Firstly, chaotic mapping is used for initialization to improve the quality of the initialized population. Secondly, the embedding of the Gaussian barebone mechanism effectively improves the diversity of the population, facilitates the communication between members, and helps the population avoid falling into local optima. Finally, the orthogonal learning strategy can extend the domain exploration and improve the solution accuracy of the algorithm. We conducted extensive experiments in the CEC2014 competition benchmark function, comparing OCBHGS with nine other metaheuristics and 12 improved algorithms. Also, the experimental results were evaluated using Wilcoxon signed-rank tests to analyze the experimental results comprehensively. In addition, OCBHGS was used to solve three constrained real-world engineering problems. The experimental results show that OCBHGS has a significant advantage in convergence speed and accuracy. As a result, OCBHGS ranks first in overall performance compared to other optimizers.
-
Yu Helong,Zhao Zisong,Zhou Jing,Heidari Ali Asghar,Chen Huiling 한국CDE학회 2023 Journal of computational design and engineering Vol.10 No.4
In recent years, the sine cosine algorithm (SCA) has become one of the popular swarm intelligence algorithms due to its simple and convenient structure. However, the standard SCA tends to fall into the local optimum when solving complex multimodal tasks, leading to unsatisfactory results. Therefore, this study presents the SCA with communication and quality enhancement, called CCEQSCA. The proposed algorithm includes two enhancement strategies: the communication and collaboration strategy (CC) and the quality enhancement strategy (EQ). In the proposed algorithm, CC strengthens the connection of SCA populations by guiding the search agents closer to the range of optimal solutions. EQ improves the quality of candidate solutions to enhance the exploitation of the algorithm. Furthermore, EQ can explore potential candidate solutions in other scopes, thus strengthening the ability of the algorithm to prevent trapping in the local optimum. To verify the capability of CCEQSCA, 30 functions from the IEEE CEC2017 are analyzed. The proposed algorithm is compared with 5 advanced original algorithms and 10 advanced variants. The outcomes indicate that it is dominant over other comparison algorithms in global optimization tasks. The work in this paper is also utilized to tackle three typical engineering design problems with excellent optimization capabilities. It has been experimentally demonstrated that CCEQSCA works as an effective tool to tackle real issues with constraints and complex search space.
-
Xing Jie,Zhao Qinqin,Chen Huiling,Zhang Yili,Zhou Feng,Zhao Hanli 한국CDE학회 2023 Journal of computational design and engineering Vol.10 No.6
We present a bee foraging behavior-driven mutational salp swarm algorithm (BMSSA) based on an improved bee foraging strategy and an unscented mutation strategy. The improved bee foraging strategy is leveraged in the follower location update phase to break the fixed range search of salp swarm algorithm, while the unscented mutation strategy on the optimal solution is employed to enhance the quality of the optimal solution. Extensive experimental results on public CEC 2014 benchmark functions validate that the proposed BMSSA performs better than nine well-known metaheuristic methods and seven state-of-the-art algorithms. The binary BMSSA (bBMSSA) algorithm is further proposed for feature selection by using BMSSA as the selection strategy and support vector machine as the classifier. Experimental comparisons on 12 UCI datasets demonstrate the superiority of bBMSSA. Finally, we collected a dataset on the return-intentions of overseas Chinese after coronavirus disease (COVID-19) through an anonymous online questionnaire and performed a case study by setting up a bBMSSA-based feature selection optimization model. The outcomes manifest that the bBMSSA-based feature selection model exhibits a conspicuous prowess, attaining an accuracy exceeding 93%. The case study shows that the development prospects, the family and job in the place of residence, seeking opportunities in China, and the possible time to return to China are the critical factors influencing the willingness to return to China after COVID-19.
연관 검색어 추천
이 검색어로 많이 본 자료
활용도 높은 자료
