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 : ( Yiming Xiang ) (검색결과 2 건)
- 무료
- 기관 내 무료
- 유료
-
An Efficient Block Index Scheme with Segmentation for Spatio-Textual Similarity Join
( Yiming Xiang ),( Yi Zhuang ),( Nan Jiang ) 한국인터넷정보학회 2017 KSII Transactions on Internet and Information Syst Vol.11 No.7
Given two collections of objects that carry both spatial and textual information in the form of tags, a Spatio-Textual-based object Similarity JOIN (ST-SJOIN) retrieves the pairs of objects that are textually similar and spatially close. In this paper, we have proposed a block index-based approach called BIST-JOIN to facilitate the efficient ST-SJOIN processing. In this approach, a dual-feature distance plane (DFDP) is first partitioned into some blocks based on four segmentation schemes, and the ST-SJOIN is then transformed into searching the object pairs falling in some affected blocks in the DFDP. Extensive experiments on real and synthetic datasets demonstrate that our proposed join method outperforms the state-of- the-art solutions.
-
ZhiJun Lyu,Jie Zhang,Ning Zhao,Qian Xiang,YiMing Song,Jie Li 한국강구조학회 2020 International Journal of Steel Structures Vol.20 No.5
The rack column is one of the essential elements in the pallet rack system. However, due to its distinctive perforation feature, it is challenging to analyze its stability using traditional theories for cold-formed steel structures. In this paper, we are interested in the comparison analysis of strength prediction on the perforated columns using fi nite element method (FEM), regression analysis (RA) and artifi cial neural network (ANN) methods respectively. First, a refi ned fi nite element (FE) model considering the perforation and nonlinearity behavior was generated and calibrated against the experimental results. Subsequently, the validated FE model was used to perform the parametric analysis for the diff erent holes in columns. Given experimental and simulated data, a regression model with an equivalent thickness was proposed for the design strength prediction of thin-walled steel perforated sections. For comparison of the RA model, two powerful tools such as the FEM and ANN are also employed to predict the design strength of diff erent perforated sections. Four indicators were used to assess the accuracy and generalization performance of the three models, including the root mean square error, the mean absolute percentage error, the correlation coeffi cient and the mean relative percentage. The obtained results show that although they both have good consistency, FEM still slightly outperforms the other two models. Since the values calculated from ANN and regression models are usually smaller than the experimental data, they are reasonably recommended as eff ective and safer design tools than FEM models from the perspective of engineering applications.
ScienceON
KISS연관 검색어 추천
이 검색어로 많이 본 자료
활용도 높은 자료
