影响因子:
2.4
ISSN:
print: 2308-0477
研究领域:
Engineering-Engineering (all)
自引率:
4.30%
Gold OA文章占比:
1.00%
原创研究文献占比:
91.30%
SCI收录类型:
Emerging Sources Citation Index (ESCI) || Scopus (CiteScore)
期刊介绍英文:
Smart Science (ISSN 2308-0477) is an international, peer-reviewed journal that publishes significant original scientific researches, and reviews and analyses of current research and science policy. We welcome submissions of high quality papers from all fields of science and from any source. Articles of an interdisciplinary nature are particularly welcomed. Smart Science aims to be among the top multidisciplinary journals covering a broad spectrum of smart topics in the fields of materials science, chemistry, physics, engineering, medicine, and biology. Smart Science is currently focusing on the topics of Smart Manufacturing (CPS, IoT and AI) for Industry 4.0, Smart Energy and Smart Chemistry and Materials. Other specific research areas covered by the journal include, but are not limited to: 1. Smart Science in the Future 2. Smart Manufacturing: -Cyber-Physical System (CPS) -Internet of Things (IoT) and Internet of Brain (IoB) -Artificial Intelligence -Smart Computing -Smart Design/Machine -Smart Sensing -Smart Information and Networks 3. Smart Energy and Thermal/Fluidic Science 4. Smart Chemistry and Materials
CiteScore:
CiteScoreSJRSNIPCiteScore排名
4.70.5690.925
学科
排名
百分位
大类:Mathematics
小类:Computational Mathematics
43 / 189
77%
大类:Mathematics
小类:Modeling and Simulation
81 / 324
75%
大类:Engineering
小类:General Engineering
81 / 307
73%
大类:Chemistry
小类:Chemistry (miscellaneous)
39 / 111
65%
大类:Chemical Engineering
小类:Fluid Flow and Transfer Processes
34 / 96
65%
大类:Energy
小类:Energy (miscellaneous)
31 / 78
60%
大类:Computer Science
小类:Computer Networks and Communications
158 / 395
60%
发文信息
WOS期刊分区
学科分类
Q2MULTIDISCIPLINARY SCIENCES
历年影响因子
2022年2.3000
2023年2.4000
历年发表
2013年31
2014年65
2015年54
2016年26
2017年38
2018年24
2019年16
2020年20
2021年39
2022年21
投稿信息
出版国家(地区):
United Kingdom
出版商:
Taylor & Francis

Smart Science - 最新文献

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Sentiment analysis technique on product reviews using Inception Recurrent Convolutional Neural Network with ResNet Transfer Learning

Pub Date : 2024-07-16 DOI: 10.1080/23080477.2024.2370210 Narahari Ajmeera, Kamakshi P

Reinforced black widow algorithm with restoration technique based on optimized deep generative adversarial network

Pub Date : 2024-07-16 DOI: 10.1080/23080477.2024.2363031 K. Praveen Kumar, C. Venkata Narasimhulu, K. Satya Prasad
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