Journal of Computational Science

Aims & Scope

Computational Science is a rapidly growing multi- and interdisciplinary field that uses advanced computing and data analysis to understand and solve complex problems.

It has reached a level of predictive capability that now firmly complements the traditional pillars of experimentation and theory.

The recent advances in experimental techniques such as detectors, on-line sensor networks and high-resolution imaging techniques, have opened up new windows into physical and biological processes at many levels of detail.

The resulting data explosion allows for detailed data driven modeling and simulation.

This new discipline in science combines computational thinking, modern computational methods, devices and collateral technologies to address problems far beyond the scope of traditional numerical methods.

Computational science typically unifies three distinct elements: • Modeling, Algorithms and Simulations (e.g. numerical and non-numerical, discrete and continuous); • Software developed to solve science (e.g., biological, physical, and social), engineering, medicine, and humanities problems; • Computer and information science that develops and optimizes the advanced system hardware, software, networking, and data management components (e.g. problem solving environments).

View Aims & Scope

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Metrics & Ranking

Impact Factor

Year	Value
2025	3.7

Journal Rank

Year	Value
2024	8153

Journal Citation Indicator

Year	Value
2024	2327

SJR (SCImago Journal Rank)

Year	Value
2024	0.697

Quartile

Year	Value
2024	Q2

h-index

Year	Value
2024	71

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Abstracting & Indexing

Journal is indexed in leading academic databases, ensuring global visibility and accessibility of our peer-reviewed research.

• Scopus
• Google Scholar
• Web of Science

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Subjects & Keywords

Journal’s research areas, covering key disciplines and specialized sub-topics in Computer Science and Mathematics, designed to support cutting-edge academic discovery.

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Most Cited Articles

The Most Cited Articles section features the journal's most impactful research, based on citation counts. These articles have been referenced frequently by other researchers, indicating their significant contribution to their respective fields.

• Twitter mood predicts the stock market

  Citation: 3376

  Authors: Johan, Huina, Xiaojun

• Multi-grade brain tumor classification using deep CNN with extensive data augmentation

  Citation: 687

  Authors: Muhammad, Salman, Khan, Wanqing, Amin, Sung Wook

• Anomaly-based intrusion detection system through feature selection analysis and building hybrid efficient model

  Citation: 483

  Authors: Shadi, Monther, Muneer Bani

• Chaotic bat algorithm

  Citation: 432

  Authors: Amir H., Xin-She

• A new feature selection method to improve the document clustering using particle swarm optimization algorithm

  Citation: 416

  Authors: Laith Mohammad, Ahamad Tajudin, Essam Said

• Modeling the spatial spread of infectious diseases: The GLobal Epidemic and Mobility computational model

  Citation: 413

  Authors: Duygu, Bruno, Hao, José J., Vittoria, Alessandro

• Nature-inspired optimization algorithms: Challenges and open problems

  Citation: 315

  Authors: Xin-She

• Pathological brain detection based on AlexNet and transfer learning

  Citation: 313

  Authors: Siyuan, Zhihai, Yu-Dong

• Emotion and sentiment analysis from Twitter text

  Citation: 286

  Authors: Kashfia, Reda

• Chaospy: An open source tool for designing methods of uncertainty quantification

  Citation: 274

  Authors: Jonathan, Hans Petter

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