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Scalable Computing-practice And Experience

Scalable Computing-practice And Experience

SCIE

国际简称：SCALABLE COMPUT-PRAC  参考译名：可扩展计算-实践与经验

  • CiteScore分区

    Q4

  • JCR分区

    Q4

基本信息：
ISSN：1895-1767
是否OA：未开放
是否预警：否
出版信息：
出版地区：ROMANIA
出版商：universitatea de vest
出版语言：English
出版周期：4 issues/year
研究方向：COMPUTER SCIENCE, SOFTWARE ENGINEERING
评价信息：
CiteScore指数：1
SJR指数：0.218
SNIP指数：0.388
发文数据：
Gold OA文章占比：98.84%
研究类文章占比：98.02%
年发文量：0
自引率：0
开源占比：0.8477
出版撤稿占比：
出版国人文章占比：0.01
OA被引用占比：0
投稿咨询 加急见刊
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Scalable Computing-practice And Experience期刊介绍

Scalable Computing - Practice and Experience "is a well-known academic journal dedicated to the field of scalable computing. Committed to developing the latest research results, practical experience, and application cases related to scalable computing. It covers a wide range of topics, including but not limited to parallel computing, distributed computing, cloud computing, big data processing, high-performance computing, etc.

In terms of content, it not only focuses on theoretical innovation, but also emphasizes technical challenges and solutions in practical applications. By publishing high-quality academic papers, review articles, and practical reports, it provides an important platform for researchers, engineers, and industry practitioners to exchange and share knowledge. For example, some research papers may explore how to optimize parallel algorithms to improve computational efficiency, or how to implement effective resource management in distributed systems; And practical reports may share successful experiences in large-scale data processing in a specific industry. It has played a positive role in promoting the development of scalable computing, facilitating cooperation and exchange between academia and industry, and continuously leading technological progress and innovation in this field.

期刊简介Scalable Computing-practice And Experience期刊介绍

《Scalable Computing-practice And Experience》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）Scalable Computing-practice And Experience Cite Score数据

  • CiteScore：1
  • SJR：0.218
  • SNIP：0.388
学科类别 分区 排名 百分位
大类：Computer Science 小类：General Computer Science Q4 201 / 239

16%

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Scalable Computing-practice And Experience 中科院分区

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, SOFTWARE ENGINEERING 计算机：软件工程 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Scalable Computing-practice And Experience JCR分区

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, SOFTWARE ENGINEERING ESCI Q4 106 / 131

19.5
学科：COMPUTER SCIENCE, SOFTWARE ENGINEERING ESCI Q4 118 / 131

10.31

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

发文数据

国家/地区发文量统计
  • 国家/地区数量
  • India96
  • Vietnam7
  • Algeria5
  • France5
  • USA5
  • Morocco4
  • PAPUA NEW GUINEA4
  • Poland4
  • Romania4
  • Bulgaria3

本刊中国学者近年发表论文

  • 1、USING GENETIC ALGORITHM TO OPTIMIZE THE TRAINING PLAN AND GAME STRATEGY OF BASKETBALL PLAYER

    Author: Qiu, Dawei

    Journal: SCALABLE COMPUTING-PRACTICE AND EXPERIENCE. 2025; Vol. 26, Issue 1, pp. 441-449. DOI: 10.12694/scpe.v26i1.3845

  • 2、RECOVERY MODELING AND ROBUSTNESS STUDY AFTER CASCADING FAILURES IN LOGISTICS-BASED NETWORK

    Author: Qian, Xiaodong; Wang, Sichen

    Journal: SCALABLE COMPUTING-PRACTICE AND EXPERIENCE. 2025; Vol. 26, Issue 1, pp. 136-150. DOI: 10.12694/scpe.v26i1.353

  • 3、THE PERSONALIZED LEARNING PATHS FOR DIGITAL MEDIA TECHNOLOGY EDUCATION BASED ON BIG DAT

    Author: Peng, Changrong; Li, Qi; Zhang, Xiaodong; Sha, Haiyan

    Journal: SCALABLE COMPUTING-PRACTICE AND EXPERIENCE. 2025; Vol. 26, Issue 1, pp. 259-268. DOI: 10.12694/scpe.v26i1.3815

  • 4、CONSTRUCTION OF AN AGRICULTURAL TRAINING EFFECTIVENESS ASSESSMENT MODEL BASED ON BIG DAT

    Author: Pan, Guangshi; Guo, Mei

    Journal: SCALABLE COMPUTING-PRACTICE AND EXPERIENCE. 2025; Vol. 26, Issue 1, pp. 287-296. DOI: 10.12694/scpe.v26i1.3549

  • 5、DESIGN OF AUTOMATIC ERROR CORRECTION SYSTEM FOR ENGLISH TRANSLATION BASED ON REINFORCEMENT LEARNING ALGORITH

    Author: Liu, Hui

    Journal: SCALABLE COMPUTING-PRACTICE AND EXPERIENCE. 2025; Vol. 26, Issue 1, pp. 297-306. DOI: 10.12694/scpe.v26i1.3552

  • 6、RESEARCH ON VEHICLE ROUTING PROBLEM WITH TIME WINDOW BASED ON IMPROVED GENETIC ALGORITH

    Author: Li, Xu; Liu, Zhengyan; Zhang, Yan

    Journal: SCALABLE COMPUTING-PRACTICE AND EXPERIENCE. 2025; Vol. 26, Issue 1, pp. 123-135. DOI: 10.12694/scpe.v26i1.3128

  • 7、INTEGRATION OF ATHLETE TRAINING MONITORING INFORMATION BASED ON DEEP LEARNIN

    Author: Li, Xi; Gao, Menglong; Hua, Jiao

    Journal: SCALABLE COMPUTING-PRACTICE AND EXPERIENCE. 2025; Vol. 26, Issue 1, pp. 269-276. DOI: 10.12694/scpe.v26i1.3839

  • 8、RESEARCH ON PERSONALIZED LEARNING RECOMMENDATION SYSTEM BASED ON MACHINE LEARNING ALGORITH

    Author: Li, Siqi; Li, Deming

    Journal: SCALABLE COMPUTING-PRACTICE AND EXPERIENCE. 2025; Vol. 26, Issue 1, pp. 432-440. DOI: 10.12694/scpe.v26i1.3844

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