Evolving Systems

Aims & Scope

"Evolving Systems" covers surveys, methodological, and application-oriented papers in the emerging area of evolving systems.

Evolving systems are inspired by the idea of system model evolution in a dynamically changing and evolving environment.

They use inheritance and gradual change with the aim of life-long learning and adaptation, self-organization including system structure evolution in order to adapt to the (unknown and unpredictable) environment as structures for information representation with the ability to fully adapt their structure and adjust their parameters.

View Aims & Scope

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Metrics & Ranking

Impact Factor

Year	Value
2025	2.7
2024	2.70

Journal Rank

Year	Value
2024	8078

Journal Citation Indicator

Year	Value
2024	947

SJR (SCImago Journal Rank)

Year	Value
2024	0.701

Quartile

Year	Value
2024	Q1

h-index

Year	Value
2024	40

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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, Engineering 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.

• Automatic tuning of hyperparameters using Bayesian optimization

  Citation: 418

  Authors: A. Helen, G.

• Application of hybrid forecast engine based intelligent algorithm and feature selection for wind signal prediction

  Citation: 197

  Authors: Mahdi, Mahdi, Mohammad Amin, Noradin

• A player unknown's battlegrounds ranking based optimization technique for power system optimization problem

  Citation: 188

  Authors: Kapil Deo, V., Vinod Kumar

• Discussion and review on evolving data streams and concept drift adapting

  Citation: 174

  Authors: Imen, Moamar, Moez, Khaled

• Survey of deep learning in breast cancer image analysis

  Citation: 146

  Authors: Taye Girma, Friedhelm, Achim, Dereje

• Generalized smart evolving fuzzy systems

  Citation: 139

  Authors: Edwin, Carlos, Stefan, Mahardhika

• Evolving spiking neural network—a survey

  Citation: 129

  Authors: Stefan, Nikola

• Evolving fuzzy granular modeling from nonstationary fuzzy data streams

  Citation: 109

  Authors: Daniel, Rosangela, Pyramo, Fernando

• Towards incremental learning of nonstationary imbalanced data stream: a multiple selectively recursive approach

  Citation: 105

  Authors: Sheng, Haibo

• Single-pass active learning with conflict and ignorance

  Citation: 100

  Authors: Edwin

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