Art
J-GLOBAL ID:201802283685328458
Reference number:18A1256121
An empirical study of PM2.5 forecasting using neural network
ニューラルネットワークを用いたPM2.5予測の経験的研究【JST・京大機械翻訳】
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Author (3):
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Material:
Volume:
2017
Issue:
SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI
Page:
1-7
Publication year:
2017
JST Material Number:
W2441A
Document type:
Proceedings
Article type:
原著論文
Country of issue:
United States (USA)
Language:
ENGLISH (EN)
Abstract/Point:
Abstract/Point
Japanese summary of the article(about several hundred characters).
All summary is available on JDreamIII(charged).
On J-GLOBAL, this item will be available after more than half a year after the record posted. In addtion, medical articles require to login to MyJ-GLOBAL.
In the recent years, a lot of ...
Thesaurus term:
Thesaurus term/Semi thesaurus term
Keywords indexed to the article.
All keywords is available on JDreamIII(charged).
On J-GLOBAL, this item will be available after more than half a year after the record posted. In addtion, medical articles require to login to MyJ-GLOBAL.
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,
,
Semi thesaurus term:
Thesaurus term/Semi thesaurus term
Keywords indexed to the article.
All keywords is available on JDreamIII(charged).
On J-GLOBAL, this item will be available after more than half a year after the record posted. In addtion, medical articles require to login to MyJ-GLOBAL.
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,
, 【Automatic Indexing@JST】
JST classification (3):
JST classification
Category name(code) classified by JST.
Traffic surveies
, Other information processing
, Examination and measurement of granular matter
Terms in the title (4):
Terms in the title
Keywords automatically extracted from the title.
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