Applied Intelligence

SCI SCIE

国际简称：APPL INTELL 参考译名：应用智能

主要研究方向：工程技术-计算机：人工智能非预警期刊审稿周期：偏慢,4-8周

《应用智能》(Applied Intelligence)是一本由Springer US出版的以工程技术-计算机：人工智能为研究特色的国际期刊，发表该领域相关的原创研究文章、评论文章和综述文章，及时报道该领域相关理论、实践和应用学科的最新发现，旨在促进该学科领域科学信息的快速交流。该期刊是一本未开放期刊，近三年没有被列入预警名单。

3区中科院分区
Q2 JCR分区
1027 年发文量
3.5 IF影响因子
未开放 是否OA
52 H-index
1991 创刊年份
Bimonthly 出版周期
English 出版语言

With a focus on research in artificial intelligence and neural networks, this journal addresses issues involving solutions of real-life manufacturing, defense, management, government and industrial problems which are too complex to be solved through conventional approaches and require the simulation of intelligent thought processes, heuristics, applications of knowledge, and distributed and parallel processing. The integration of these multiple approaches in solving complex problems is of particular importance.

The journal presents new and original research and technological developments, addressing real and complex issues applicable to difficult problems. It provides a medium for exchanging scientific research and technological achievements accomplished by the international community.

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Applied Intelligence期刊信息

ISSN：0924-669X
出版语言：English
是否OA：未开放
E-ISSN：1573-7497
出版地区：NETHERLANDS
是否预警：否
出版商：Springer US
出版周期：Bimonthly
创刊时间：1991
开源占比：0.0604
Gold OA文章占比：9.92%
OA被引用占比：
出版国人文章占比：0
出版撤稿占比：
研究类文章占比：100.00%

Applied Intelligence CiteScore评价数据（2026年6月最新版）

CiteScore

SJR

SNIP

CiteScore 指数

9.1

0.889

1.194

学科类别	分区	排名	百分位
大类：Computer Science 小类：Artificial Intelligence	Q1	110 / 570	80%

名词解释：CiteScore 是衡量期刊所发表文献的平均受引用次数，是在 Scopus 中衡量期刊影响力的另一个指标。当年CiteScore 的计算依据是期刊最近4年（含计算年度）的被引次数除以该期刊近四年发表的文献数。例如，2022年的 CiteScore 计算方法为：2022年的 CiteScore =2019-2022年收到的对2019-2022年发表的文件的引用数量÷2019-2022年发布的文献数量注：文献类型包括：文章、评论、会议论文、书籍章节和数据论文。

Applied Intelligence中科院评价数据

《新锐期刊分区表》（2026年3月发布）

Top期刊	综述期刊	大类学科		小类学科
否	否	计算机科学	3区	COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE 计算机：人工智能	3区

Applied Intelligence JCR评价数据

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	SCIE	Q2	102 / 210	51.7
学科：COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE	SCIE	Q3	121 / 210	42.62

Applied Intelligence历年数据统计

影响因子

中科院分区

Applied Intelligence中国学者发文选摘

1、FMD-TransUNet: abdominal multi-organ segmentation based on frequency domain multi-axis representation learning and dual attention mechanism
Author: Lu, Fang; Xu, Jingyu; Sun, Qinxiu; Lou, Qiong

Journal: APPLIED INTELLIGENCE. 2026; Vol. 56, Issue 6, pp. -. DOI: 10.1007/s10489-026-07240-y
2、Unsupervised multidimensional sample dynamic optimization for cross-modal hashin
Author: Du, Hao; Liu, Li; Zhang, Huaxiang; Liu, Dongmei; Du, Kang

Journal: APPLIED INTELLIGENCE. 2026; Vol. 56, Issue 6, pp. -. DOI: 10.1007/s10489-026-07161-w
3、Graph diffusion arithmetic feature interaction transformer with temporal information for bitcoin anti-money launderin
Author: Li, Meng; Jia, Lu; Ma, Xinyi; Su, Xinqiao

Journal: APPLIED INTELLIGENCE. 2026; Vol. 56, Issue 6, pp. -. DOI: 10.1007/s10489-026-07232-y
4、DAMT-Former: Dynamic Attention and Multi-scale Temporal Former for Facial Expression Recognitio
Author: Guo, Daipeng; Xu, Fei

Journal: APPLIED INTELLIGENCE. 2026; Vol. 56, Issue 6, pp. -. DOI: 10.1007/s10489-026-07195-0
5、Parameter adaptive competitive differential evolution with local searc
Author: Zhong, Rui; Wang, Zhongmin; Xiao, Yaning; Zhang, Yujun; Jacob Lian, Junbo; Yu, Jun; Cai, Zhennao; Pan, Zhiyong; Chen, Huiling; Yu, Sudan

Journal: APPLIED INTELLIGENCE. 2026; Vol. 56, Issue 5, pp. -. DOI: 10.1007/s10489-026-07141-0
6、Optimized road traffic forecasting via multi-convolutional fusion and spatio-temporal feature extraction networks: An adaptive, anomaly-responsive framewor
Author: Wang, Zhiwen; Zeng, Jingxiao; Li, Long; Yang, Kangkang; Shi, Yaoke; Ling, Guobi; Sun, Jingjing

Journal: APPLIED INTELLIGENCE. 2026; Vol. 56, Issue 5, pp. -. DOI: 10.1007/s10489-026-07219-9
7、RETRACTION: Semi-supervised medical image classification via increasing prediction diversit
Author: Liu, Peng; Qian, Wenhua; Cao, Jinde; Xu, Dan

Journal: APPLIED INTELLIGENCE. 2026; Vol. 56, Issue 5, pp. -. DOI: 10.1007/s10489-026-07236-8
8、MDEbert-DTA: Drug-Target Affinity Prediction using Multimodal Contrastive Learning and Dynamic Graph Aggregatio
Author: Yang, Huaizhou; Tong, Xiaohan

Journal: APPLIED INTELLIGENCE. 2026; Vol. 56, Issue 5, pp. -. DOI: 10.1007/s10489-026-07096-2