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Ai

Ai

SCIE

国际简称:Ai  参考译名:人工智能

  • 中科院分区

    2区

  • CiteScore分区

    Q2

  • JCR分区

    Q1

基本信息:
ISSN:2673-2688
是否OA:未开放
是否预警:否
TOP期刊:是
出版信息:
出版地区:Switzerland
出版商:MDPI AG
出版语言:English
研究方向:Computer Science-Artificial Intelligence
评价信息:
影响因子:6.5
CiteScore指数:7.3
SJR指数:1.124
SNIP指数:1.842
发文数据:
Gold OA文章占比:100.00%
研究类文章占比:87.32%
年发文量:339
英文简介 期刊介绍 CiteScore数据 中科院SCI分区 JCR分区 发文数据 常见问题

英文简介Ai期刊介绍

AI Magazine, also known as Artificial Intelligence Magazine, is a prestigious international academic journal that focuses on cutting-edge research and theoretical development in the field of artificial intelligence. Since its inception, the magazine has been one of the most influential publications in the field of artificial intelligence, published by Elsevier Press. AI magazine is committed to publishing high-quality original research papers covering various aspects of artificial intelligence, including but not limited to machine learning, deep learning, natural language processing, computer vision, robotics, knowledge representation and reasoning, intelligent system design, and more.

The distinctive feature of this magazine lies in its rigorous screening and publication of innovative and high-quality research in the field of artificial intelligence. AI magazine not only focuses on fundamental theoretical research, but also attaches importance to research that can promote the application of artificial intelligence technology in the real world. The journal encourages the submission of articles with innovation, theoretical depth, and practical value, providing a platform for researchers and practitioners worldwide to exchange and share the latest research results. As an important academic publication in the field of artificial intelligence, AI magazine has extremely high value for both academic research and industry practice.

期刊简介Ai期刊介绍

《Ai》是一本计算机科学优秀杂志。致力于发表原创科学研究结果,并为计算机科学各个领域的原创研究提供一个展示平台,以促进计算机科学领域的的进步。该刊鼓励先进的、清晰的阐述,从广泛的视角提供当前感兴趣的研究主题的新见解,或审查多年来某个重要领域的所有重要发展。该期刊特色在于及时报道计算机科学领域的最新进展和新发现新突破等。该刊近一年未被列入预警期刊名单,目前已被权威数据库SCIE收录,得到了广泛的认可。

该期刊投稿重要关注点:

Cite Score数据(2026年6月最新版)Ai Cite Score数据

  • CiteScore:7.3
  • SJR:1.124
  • SNIP:1.842
学科类别 分区 排名 百分位
大类:Computer Science 小类:Artificial Intelligence Q2 147 / 570

74%

CiteScore 是由Elsevier(爱思唯尔)推出的另一种评价期刊影响力的文献计量指标。反映出一家期刊近期发表论文的年篇均引用次数。CiteScore以Scopus数据库中收集的引文为基础,针对的是前四年发表的论文的引文。CiteScore的意义在于,它可以为学术界提供一种新的、更全面、更客观地评价期刊影响力的方法,而不仅仅是通过影响因子(IF)这一单一指标来评价。

历年Cite Score趋势图

中科院SCI分区Ai 中科院分区

《新锐期刊分区表》(2026年3月发布) 综述期刊:否 Top期刊:否
大类学科 分区 小类学科 分区
计算机科学 2区 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE 计算机:人工智能 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS 计算机:跨学科应用 3区 3区
期刊分区表(2025年3月升级版) 综述期刊:否 Top期刊:否
大类学科 分区 小类学科 分区
计算机科学 4区 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE 计算机:人工智能 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS 计算机:跨学科应用 4区 4区

中科院分区表 是以客观数据为基础,运用科学计量学方法对国际、国内学术期刊依据影响力进行等级划分的期刊评价标准。它为我国科研、教育机构的管理人员、科研工作者提供了一份评价国际学术期刊影响力的参考数据,得到了全国各地高校、科研机构的广泛认可。

中科院分区表 将所有期刊按照一定指标划分为1区、2区、3区、4区四个层次,类似于“优、良、及格”等。最开始,这个分区只是为了方便图书管理及图书情报领域的研究和期刊评估。之后中科院分区逐步发展成为了一种评价学术期刊质量的重要工具。

历年中科院分区趋势图

JCR分区Ai JCR分区

2025-2026年最新版
按JCI指标学科分区 收录子集 分区 排名 百分位
学科:COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE ESCI Q1 47 / 210

77.9

学科:COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS ESCI Q1 37 / 185

80.3

学科:COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE ESCI Q2 76 / 210

64.05

学科:COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS ESCI Q2 84 / 185

54.86

2023-2024年最新版
按JCI指标学科分区 收录子集 分区 排名 百分位
学科:COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE ESCI Q2 86 / 197

56.6

学科:COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS ESCI Q2 65 / 169

61.8

学科:COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE ESCI Q3 100 / 198

49.75

学科:COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS ESCI Q3 90 / 169

47.04

JCR分区的优势在于它可以帮助读者对学术文献质量进行评估。不同学科的文章引用量可能存在较大的差异,此时单独依靠影响因子(IF)评价期刊的质量可能是存在一定问题的。因此,JCR将期刊按照学科门类和影响因子分为不同的分区,这样读者可以根据自己的研究领域和需求选择合适的期刊。

历年影响因子趋势图

本刊中国学者近年发表论文

  • 1、Etch-ViGen: A Video Generation Model for Etching Simulatio

    Author: Ding, Li; Shao, Hua; Li, Zhiqiang; Liu, Nan; Chen, Rui; Yao, Zhenjie

    Journal: AI. 2026; Vol. 7, Issue 4, pp. -. DOI: 10.3390/ai7040149

  • 2、VGPO-MCTS: Distilling Step-Level Supervision from Value-Guided Tree Search for Mathematical Reasonin

    Author: Wu, Pin; Zhu, Yufei; Wang, Huiyan

    Journal: AI. 2026; Vol. 7, Issue 4, pp. -. DOI: 10.3390/ai7040146

  • 3、A GNSS-Vision Integrated Autonomous Navigation System for Trellis Orchard Transportation Robot

    Author: Liu, Huaiyang; Gu, Haiyang; Wang, Yong; Zhong, Tianjiao; Tian, Tong; Geng, Changxing

    Journal: AI. 2026; Vol. 7, Issue 4, pp. -. DOI: 10.3390/ai7040125

  • 4、Real-Time Constrained Visual Servoing for Agricultural Harvesting Robots via MPC-Guided Reinforcement Learnin

    Author: Gao, Liangzheng; Feng, Qingchun; Chen, Shiqi; Yang, Zhijie; Fan, Fengcui; Chen, Lin; Zhao, Chunjiang

    Journal: AI. 2026; Vol. 7, Issue 4, pp. -. DOI: 10.3390/ai7040124

  • 5、Just-in-Time Historical State Reconstruction for Low-Latency Financial Trading with Large Language Model

    Author: Van, Dong Hoang; Karim, Md Monjurul; Qu, Qiang

    Journal: AI. 2026; Vol. 7, Issue 4, pp. -. DOI: 10.3390/ai7040117

  • 6、Trust Triangle: A Reliability-Validity-Generation Framework for Explainable Credit Card Fraud Detection with RAG-Enhanced LLMs Reasonin

    Author: Shen, Jin-Ching; Su, Nai-Ching; Lin, Yi-Bing

    Journal: AI. 2026; Vol. 7, Issue 3, pp. -. DOI: 10.3390/ai7030114

  • 7、A Real-Time Laryngeal Disease Diagnosis Algorithm on Edge-A

    Author: Liu, Yarong; Leng, Dong; Xie, Xiaolan; Li, Zhiyu

    Journal: AI. 2026; Vol. 7, Issue 3, pp. -. DOI: 10.3390/ai7030113

  • 8、Artificial Intelligence-Simulated Cognition of a Pedestrian Assessing a Built Environmen

    Author: Belaroussi, Rachid; Salingaros, Nikos A

    Journal: AI. 2026; Vol. 7, Issue 3, pp. -. DOI: 10.3390/ai7030110

投稿常见问题