← 返回列表 SCI 期刊 计算机科学 Nat Mach Intell

Nature Machine Intelligence

Nat Mach Intell

ISSN 2522-5839
SCIE Q1 新锐1区 Top期刊 开放获取 计算机科学
影响因子 2026
29.8
↑ 5.9
5年均分
36
5-Year IF
H 指数
146
H-Index
年发文量
196
Articles / Year
出刊频率
12 issues per year
Pub. Frequency
创刊年份
2018
Founded Year
出版商
Nature Portfolio
Publisher
出版国家
UK
Country
投稿参考 & 用户评分
🏆 期刊声誉
暂无
综合口碑评分,点击星星参与
审稿速度
暂无
暂无实测数据,欢迎分享经验
💰 版面费用
系统
暂无
官方APC $11,690 USD 约¥84,753
中科院分区
2026新锐分区 新体系
大类1区
计算机科学Computer Science
小类1区
计算机:人工智能AI & Machine Learning
中科院2025年分区 传统体系
大类1区
计算机科学Computer Science
小类1区
计算机:人工智能AI & Machine Learning
Scopus 指标
CiteScore
40.9
综合引用得分
SJR
6.902 Q1
SCImago Journal Rank
SNIP
6.392
Source Normalized Impact
JCI
3.62
Journal Citation Indicator
数据来源:Scopus (CiteScore · SJR · SNIP) · Clarivate (JCI)。指标年份:2026年6月最新版。
期刊简介

Nature Machine Intelligence is a premier monthly journal published by Springer Nature, dedicated to the rapidly evolving intersection of artificial intelligence, machine learning, and the broader natural sciences. With an ISSN of 2522-5839 and a 2026 Impact Factor of 25.8980, the journal holds a distinguished Q1 ranking in the JCR, reflecting its status as one of the most influential and highly cited publications in its field. The journal’s scope encompasses fundamental advances in machine learning algorithms, data-driven models, and intelligent systems, with a strong emphasis on applications that address complex scientific challenges across disciplines such as physics, chemistry, biology, medicine, engineering, and environmental science. It publishes a diverse range of article types, including original research articles, reviews, perspectives, and commentaries, all of which undergo rigorous peer review to ensure high scientific quality and novelty. The target audience includes academic researchers, data scientists, engineers, and industry professionals seeking cutting-edge developments in machine intelligence and its practical deployment. A notable feature of Nature Machine Intelligence is its hybrid open access model, allowing authors to publish under a Creative Commons license for immediate open access or through the traditional subscription route. The journal also offers dedicated content such as News & Views, editorials, and interviews with leading figures, fostering interdisciplinary dialogue. Its exceptional impact factor and top-tier quartile positioning underscore its role as a leading venue for transformative research that bridges machine learning with real-world scientific discovery and technological innovation.

历年影响因子 & 年发文量

上述信息均来源于网络,以官方发布为准,仅供参考。如有建议,欢迎反馈

生物行 © 2002–2026  All Rights Reserved.