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期刊名字 | NEURAL NETWORKS NEURAL NETWORKS （此期刊被最新的JCR期刊SCIE收录） LetPub评分 8.4
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声誉 8.7 影响力 8.0 速度 8.0 | |||||||||||||||||||||
| 期刊ISSN | 0893-6080 | 微信扫码收藏此期刊 | ||||||||||||||||||||
| E-ISSN | 1879-2782 | |||||||||||||||||||||
| 2022-2023最新影响因子 （数据来源于搜索引擎） | 7.8 点击查看影响因子趋势图 | |||||||||||||||||||||
| 实时影响因子 | 截止2023年6月16日：7.779 | |||||||||||||||||||||
| 2022-2023自引率 | 7.70%点击查看自引率趋势图 | |||||||||||||||||||||
| 五年影响因子 | 8.4 | |||||||||||||||||||||
| h-index | 128 | |||||||||||||||||||||
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| 期刊简介 | Neural Networks is the archival journal of the world's three oldest neural modeling societies: the International Neural Network Society (INNS), the European Neural Network Society (ENNS), and the Japanese Neural Network Society (JNNS). A subscription to the journal is included with membership in each of these societies. Neural Networks provides a forum for developing and nurturing an international community of scholars and practitioners who are interested in all aspects of neural networks and related approaches to computational intelligence. Neural Networks welcomes high quality submissions that contribute to the full range of neural networks research, from behavioral and brain modeling, learning algorithms, through mathematical and computational analyses, to engineering and technological applications of systems that significantly use neural network concepts and techniques. This uniquely broad range facilitates the cross-fertilization of ideas between biological and technological studies, and helps to foster the development of the interdisciplinary community that is interested in biologically-inspired computational intelligence. Accordingly, Neural Networks editorial board represents experts in fields including psychology, neurobiology, computer science, engineering, mathematics, and physics. The journal publishes articles, letters and reviews, as well as letters to the editor, editorials, current events, software surveys, and patent information. Articles are published in one of five sections: Cognitive Science, Neuroscience, Learning Systems, Mathematical and Computational Analysis, Engineering and Applications. | |||||||||||||||||||||
| 期刊官方网站 | http://www.elsevier.com/wps/find/journaldescription.cws_home/841/description | |||||||||||||||||||||
| 期刊投稿网址 | https://www.editorialmanager.com/NEUNET | |||||||||||||||||||||
| 期刊语言要求 | Language Please write your text in good English (American or British usage is accepted, but not a mixture of these). Authors who feel their English language manuscript may require editing to eliminate possible grammatical or spelling errors and to conform to correct scientific English may wish to use the English Language Editing service. 经LetPub语言功底雄厚的美籍native English speaker精心编辑的稿件，不仅能满足NEURAL NETWORKS的语言要求，还能让NEURAL NETWORKS编辑和审稿人得到更好的审稿体验，让稿件最大限度地被NEURAL NETWORKS编辑和审稿人充分理解和公正评估。LetPub的专业SCI论文编辑服务（包括SCI论文英语润色，同行资深专家修改润色，SCI论文专业翻译，SCI论文格式排版，专业学术制图等）帮助作者准备稿件，已助力全球15万+作者顺利发表论文。部分发表范例可查看：服务好评 论文致谢 。 提交文稿 | |||||||||||||||||||||
| 是否OA开放访问 | No | |||||||||||||||||||||
| 通讯方式 | PERGAMON-ELSEVIER SCIENCE LTD, THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD, ENGLAND, OX5 1GB | |||||||||||||||||||||
| 出版商 | Elsevier Ltd | |||||||||||||||||||||
| 涉及的研究方向 | 工程技术-计算机：人工智能 | |||||||||||||||||||||
| 出版国家或地区 | ENGLAND | |||||||||||||||||||||
| 出版语言 | English | |||||||||||||||||||||
| 出版周期 | Monthly | |||||||||||||||||||||
| 出版年份 | 1988 | |||||||||||||||||||||
| 年文章数 | 402点击查看年文章数趋势图 | |||||||||||||||||||||
| Gold OA文章占比 | 12.07% | |||||||||||||||||||||
| 研究类文章占比： 文章 ÷（文章 + 综述） | 98.51% | |||||||||||||||||||||
| WOS期刊SCI分区 （ 2022-2023年最新版） | WOS分区等级：1区
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| 中科院《国际期刊预警 名单（试行）》名单 | 2023年01月发布的2023版：不在预警名单中 2021年12月发布的2021版：不在预警名单中 2021年01月发布的2020版：不在预警名单中 | |||||||||||||||||||||
| 中科院SCI期刊分区 （ 2022年12月最新升级版） | 点击查看中科院SCI期刊分区趋势图
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| 中科院SCI期刊分区 （ 2021年12月基础版） |
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| 中科院SCI期刊分区 （ 2021年12月升级版） |
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| 中科院SCI期刊分区 （ 2020年12月旧的升级版） |
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| SCI期刊收录coverage | Science Citation Index Expanded (SCIE) (2020年1月，原SCI撤销合并入SCIE，统称SCIE) Scopus (CiteScore) | |||||||||||||||||||||
| PubMed Central (PMC)链接 | http://www.ncbi.nlm.nih.gov/nlmcatalog?term=0893-6080%5BISSN%5D | |||||||||||||||||||||
| 平均审稿速度 | 网友分享经验： 平均12.0个月 来源Elsevier官网： 平均10.5周 | |||||||||||||||||||||
| 平均录用比例 | 网友分享经验： 较易 | |||||||||||||||||||||
| LetPub助力发表 | 经LetPub编辑的稿件平均录用比例是未经润色的稿件的1.5倍，平均审稿时间缩短40%。众多作者在使用LetPub的专业SCI论文编辑服务（包括SCI论文英语润色，同行资深专家修改润色，SCI论文专业翻译，SCI论文格式排版，专业学术制图等）后论文在NEURAL NETWORKS顺利发表。
快看看作者怎么说吧：服务好评 论文致谢 | |||||||||||||||||||||
| 在线出版周期 | 来源Elsevier官网： 平均7.1周 | |||||||||||||||||||||
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| 中国学者近期发表的论文 | |
| 1. | Lifelong learning with Shared and Private Latent Representations learned through synaptic intelligence Author: Yang, Yang; Huang, Jie; Hu, Dexiu Journal: NEURAL NETWORKS. 2023; Vol. 163, Issue , pp. 165-177. DOI: 10.1016/j.neunet.2023.04.005 PubMed DOI |
| 2. | Collaborative-guided spectral abundance learning with bilinear mixing model for hyperspectral subpixel target detection Author: Zhu, Dehui; Du, Bo; Hu, Meiqi; Dong, Yanni; Zhang, Liangpei Journal: NEURAL NETWORKS. 2023; Vol. 163, Issue , pp. 205-218. DOI: 10.1016/j.neunet.2023.02.002 PubMed DOI |
| 3. | Unsupervised graph-level representation learning with hierarchical contrasts Author: Ju, Wei; Gu, Yiyang; Luo, Xiao; Wang, Yifan; Yuan, Haochen; Zhong, Huasong; Zhang, Ming Journal: NEURAL NETWORKS. 2023; Vol. 158, Issue , pp. 359-368. DOI: 10.1016/j.neunet.2022.11.019 PubMed DOI |
| 4. | Monte Carlo Ensemble Neural Network for the diagnosis of Alzheimer's disease Author: Liu, Chaoqiang; Huang, Fei; Qiu, Anqi Journal: NEURAL NETWORKS. 2023; Vol. 159, Issue , pp. 14-24. DOI: 10.1016/j.neunet.2022.10.032 PubMed DOI |
| 5. | Factorizing time-heterogeneous Markov transition for temporal recommendation? Author: Wen, Wen; Wang, Wencui; Hao, Zhifeng; Cai, Ruichu Journal: NEURAL NETWORKS. 2023; Vol. 159, Issue , pp. 84-96. DOI: 10.1016/j.neunet.2022.11.032 PubMed DOI |
| 6. | Efficient Perturbation Inference and Expandable Network for continual learning Author: Du, Fei; Yang, Yun; Zhao, Ziyuan; Zeng, Zeng Journal: NEURAL NETWORKS. 2023; Vol. 159, Issue , pp. 97-106. DOI: 10.1016/j.neunet.2022.10.030 PubMed DOI |
| 7. | Variable three-term conjugate gradient method for training artificial neural networks Author: Kim, Hansu; Wang, Chuxuan; Byun, Hyoseok; Hu, Weifei; Kim, Sanghyuk; Jiao, Qing; Lee, Tah Hee Journal: NEURAL NETWORKS. 2023; Vol. 159, Issue , pp. 125-136. DOI: 10.1016/j.neunet.2022.12.001 PubMed DOI |
| 8. | Representation learning for continuous action spaces is beneficial for efficient policy learning Author: Zhao, Tingting; Wang, Ying; Sun, Wei; Chen, Yarui; Niu, Gang; Sugiyama, Masashi Journal: NEURAL NETWORKS. 2023; Vol. 159, Issue , pp. 137-152. DOI: 10.1016/j.neunet.2022.12.009 PubMed DOI |
| 9. | Path reliability-based graph attention networks Author: Li, Yayang; Liang, Shuqing; Jiang, Yuncheng Journal: NEURAL NETWORKS. 2023; Vol. 159, Issue , pp. 153-160. DOI: 10.1016/j.neunet.2022.11.021 PubMed DOI |
| 10. | An explainable autoencoder with multi-paradigm fMRI fusion for identifying differences in dynamic functional connectivity during brain development Author: Xu, Faming; Qiao, Chen; Zhou, Huiyu; Calhoun, Vince D.; Stephen, Julia M.; Wilson, Tony W.; Wang, Yuping Journal: NEURAL NETWORKS. 2023; Vol. 159, Issue , pp. 185-197. DOI: 10.1016/j.neunet.2022.12.007 PubMed DOI |
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