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迷路的小孩子

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[交流] 谁帮忙检索篇论文是否SCI,web of science的检索信息能贴下吗,谢谢。 已有2人参与

Differentiation of Mechanical Damages of Rice Plants Using E-Nose,这篇论文SCI检索吗,谁能把WEB OF SCIENCE检索信息贴出来啊。
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3楼: Originally posted by nuaawq at 2013-07-16 13:29:45
DIFFERENTIATION OF MECHANICAL DAMAGES OF RICE PLANTS USING E-NOSE  
Author(s): Zhou, B (Zhou, Bo) ; Wang, J (Wang, Jun)  
Source: INTELLIGENT AUTOMATION AND SOFT COMPUTING  Volume: 18   Issue: 5    ...

谢谢,请问是SCI检索吗。
4楼2013-07-17 10:19:22
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nuaawq

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小木虫: 金币+0.5, 给个红包,谢谢回帖
DIFFERENTIATION OF MECHANICAL DAMAGES OF RICE PLANTS USING E-NOSE  
Author(s): Zhou, B (Zhou, Bo)[ 1 ] ; Wang, J (Wang, Jun)[ 1 ]  
Source: INTELLIGENT AUTOMATION AND SOFT COMPUTING  Volume: 18   Issue: 5   Special Issue: SI   Pages: 443-451   Published: 2012  
Times Cited: 0 (from Web of Science)  
Cited References: 19      [ view related records ]     Citation Map      
Abstract: Plants change the emission of induced volatiles in response to damage and herbivore attack, and monitoring the change of such volatiles could provide a nondestructive means of plant health measurement. Current monitoring techniques for plant volatiles are time-consuming and costly. The main objective of this research is to figure out whether electronic nose (e-nose) technique can be used to differentiate rice plants with different degrees of mechanical damage. A portable e-nose (PEN2) is used to characterize and classify rice plants subjected to three degrees of mechanical damage compared with undamaged control plants. Principle component analysis (PCA), Linear discriminant analysis (LDA), Stepwise discriminant analysis (SDA), and Back-propagation neural network (BPNN) are applied to evaluate the data. Different degrees of damaged rice plants are better distinguished using LDA than using PCA. The average correction ratio of testing set of BPNN is 75%. The results obtained indicate that it is possible to classify different degrees of damaged rice plants using e-nose signals. This study demonstrates the feasibility of using an e-nose to rice plant damage assessment.  
Accession Number: WOS:000314855700002  
Document Type: Article  
Language: English  
Author Keywords: Rice plant; Mechanical damage; Electronic nose; Crop inspection  
KeyWords Plus: ELECTRONIC NOSE; NILAPARVATA-LUGENS; VOLATILE EMISSIONS; DISCRIMINATION; QUALITY  
Reprint Address: Wang, J (reprint author)  Zhejiang Univ, Dept Biosyst Engn, 268 Kaixuan Rd, Hangzhou 310029, Zhejiang, Peoples R China.
  Organization-Enhanced Name(s)
    Zhejiang University  

Addresses:  [ 1 ] Zhejiang Univ, Dept Biosyst Engn, Hangzhou 310029, Zhejiang, Peoples R China
  Organization-Enhanced Name(s)
    Zhejiang University  

E-mail Addresses: zjzhobo@163.com; jwang@zju.edu.cn  
Publisher: AUTOSOFT PRESS, 18015 BOLLIS HILL, SAN ANTONIO, TX 78258 USA  
Web of Science Categories: Automation & Control Systems; Computer Science, Artificial Intelligence  
Research Areas: Automation & Control Systems; Computer Science  
IDS Number: 088RV  
ISSN: 1079-8587
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