Applied Soft Computing

Aims & Scope

Applied Soft Computing is an international journal promoting an integrated view of soft computing to solve real life problems.

Soft computing is a collection of methodologies, which aim to exploit tolerance for imprecision, uncertainty and partial truth to achieve tractability, robustness and low solution cost.

The focus is to publish the highest quality research in application and convergence of the areas of Fuzzy Logic, Neural Networks, Evolutionary Computing, Rough Sets and other similar techniques to address real world complexities.

Applied Soft Computing is a rolling publication: articles are published as soon as the editor-in-chief has accepted them.

Therefore, the web site will continuously be updated with new articles and the publication time will be short.

Major Topics: The scope of this journal covers the following soft computing and related techniques, interactions between several soft computing techniques, and their industrial applications: • Ant Colony • Chaos Theory • Evolutionary Computing • Fuzzy Computing • Hybrid Methods • Immunological Computing • Morphic Computing • Neuro Computing • Particle Swarm • Probabilistic Computing • Rough Sets • Wavelet

View Aims & Scope

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Metrics & Ranking

Impact Factor

Year	Value
2025	6.6

Journal Rank

Year	Value
2024	2356

Journal Citation Indicator

Year	Value
2024	27020

SJR (SCImago Journal Rank)

Year	Value
2024	1.511

Quartile

Year	Value
2024	Q1

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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, 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.

• On the performance of artificial bee colony (ABC) algorithm

  Citation: 2951

  Authors: D., B.

• A survey on deep learning techniques for image and video semantic segmentation

  Citation: 1285

  Authors: Alberto, Sergio, Sergiu, Victor, Pablo, Jose

• Investigating the impact of data normalization on classification performance

  Citation: 1234

  Authors: Dalwinder, Birmohan

• Differential evolution algorithm with ensemble of parameters and mutation strategies

  Citation: 1177

  Authors: R., P.N., Q.K., M.F.

• Cuckoo Optimization Algorithm

  Citation: 909

  Authors: Ramin

• Financial time series forecasting with deep learning : A systematic literature review: 2005–2019

  Citation: 890

  Authors: Omer Berat, Mehmet Ugur, Ahmet Murat

• Mine blast algorithm: A new population based algorithm for solving constrained engineering optimization problems

  Citation: 824

  Authors: Ali, Ardeshir, Hadi, Mohd

• A novel clustering approach: Artificial Bee Colony (ABC) algorithm

  Citation: 812

  Authors: Dervis, Celal

• Whale optimization approaches for wrapper feature selection

  Citation: 693

  Authors: Majdi, Seyedali

• A novel particle swarm optimization algorithm with adaptive inertia weight

  Citation: 676

  Authors: Ahmad, Mohammad Mehdi, Reza

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