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 : Jiajia Tao (검색결과 2 건)
- 무료
- 기관 내 무료
- 유료
-
Hydroxide MgSn(OH)6: A Promising New Photocatalyst for Methyl Orange Degradation
Jiajia Tao,Zhaoqi Sun,Miao Zhang,Gang He,Xiaoshuang Chen 대한금속·재료학회 2017 ELECTRONIC MATERIALS LETTERS Vol.13 No.4
Highly crystalline hydroxide MgSn(OH)6 (MHS) polyhedral particleswere synthesized by changing reaction time (10, 15 and 20 h) in ahydrothermal process. The structural and morphological poperties ofobtained samples were characterized by X-ray diffraction (XRD),scanning electron microscopy (SEM), and UV-vis diffuse reflectancespectroscopy (DRS). The photocatalytic activity of the MHS wasfurther evaluated by the degradation of methyl orange (MO) underultraviolet (UV) light illumination. Compared with commercial TiO2(Degussa P25), the MHS prepared for 15 h showed similar degradationefficiency of methyl orange (MO), mainly due to its higher specificsurface area (55 m2g−1) and better optical properties.
-
An Adaptive Cellular Genetic Algorithm Based on Selection Strategy for Test Sheet Generation
Ankun Huang,Dongmei Li,Jiajia Hou,Tao Bi 보안공학연구지원센터 2015 International Journal of Hybrid Information Techno Vol.8 No.9
Intelligent test sheet generation is a multi-objective constrained optimization problem. Genetic algorithm based on groups search strategy can provide a better solution for multi-objective optimization. Traditional genetic algorithm in test sheet generation process has many drawbacks, such as poor convergence, low fitness and high exposure times. To solve these problems, this paper proposes an adaptive cellular genetic algorithm based on selection strategy. Selection strategy can adaptively determine candidate test items set and the conceptual granularities according to the desired concept scope. Then, a new cellular population is formed by candidate test items. After evolution by the rule, genetic algorithms are executed. The experimental results show that the proposed algorithm gets rid of tests that do not meet the requirements which can reduce knowledge related errors, lower the exposure of tests, and increase the possibility of escape from local optima. In general, the algorithm proposed in this paper effectively improves the convergence speed as well as generates test papers more in line with people's demands.
연관 검색어 추천
이 검색어로 많이 본 자료
활용도 높은 자료
