International Journal of Computational Intelligence and Applications

Aims & Scope

The International Journal of Computational Intelligence and Applications, IJCIA, is a refereed journal dedicated to the theory and applications of computational intelligence (artificial neural networks, fuzzy systems, evolutionary computation and hybrid systems).

The main goal of this journal is to provide the scientific community and industry with a vehicle whereby ideas using two or more conventional and computational intelligence based techniques could be discussed.

The IJCIA welcomes original works in areas such as neural networks, fuzzy logic, evolutionary computation, pattern recognition, hybrid intelligent systems, symbolic machine learning, statistical models, image/audio/video compression and retrieval.

The IJCIA greatly encourages new ideas, combining two or more areas, such as neuro-fuzzy, neuro-symbolic, neuro-evolutionary, neuro-symbolic, neuro-pattern recognition, fuzzy-evolutionary, evolutionary-symbolic, fuzzy-evolutionary, evolutionary-symbolic, fuzzy-symbolic, etc. to be submitted.

View Aims & Scope

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Metrics & Ranking

Impact Factor

Year	Value
2025	1.3
2024	0.80

Journal Rank

Year	Value
2024	17366

Journal Citation Indicator

Year	Value
2024	180

SJR (SCImago Journal Rank)

Year	Value
2024	0.279

Quartile

Year	Value
2024	Q3

h-index

Year	Value
2024	26

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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.

• Convolutional Neural Networks for Water Body Extraction from Landsat Imagery

  Citation: 91

  Authors: Long, Zhiyin, Shengwei, Feiyue, Jianli, Jun

• Speeding up the Hyperparameter Optimization of Deep Convolutional Neural Networks

  Citation: 89

  Authors: Tobias, Nicolás, Sven, Stefan

• Hybrid Grey Wolf Optimizer Using Elite Opposition-Based Learning Strategy and Simplex Method

  Citation: 84

  Authors: Sen, Qifang, Yongquan

• TWO-DIMENSIONAL IIR FILTER DESIGN WITH MODERN SEARCH HEURISTICS: A COMPARATIVE STUDY

  Citation: 65

  Authors: SWAGATAM, AMIT

• A Comprehensive Comparison on Evolutionary Feature Selection Approaches to Classification

  Citation: 62

  Authors: Bing, Mengjie, Will N.

• EVOLUTIONARY OPTIMIZATION <font>(EvOpt)</font>: A BRIEF REVIEW AND ANALYSIS

  Citation: 58

  Authors: RUHUL, JOARDER, CHARLES

• ONLINE CLASS IMBALANCE LEARNING AND ITS APPLICATIONS IN FAULT DETECTION

  Citation: 56

  Authors: SHUO, LEANDRO L., XIN

• Transformer-Based Deep Learning Model for Stock Price Prediction: A Case Study on Bangladesh Stock Market

  Citation: 56

  Authors: Tashreef, Anika Bintee, Muhammad, Md. Mainul, Maishameem Meherin, Shahidul Islam, Mohammad Shafiul

• IMMUNE AND NEURAL NETWORK MODELS: THEORETICAL AND EMPIRICAL COMPARISONS

  Citation: 53

  Authors: LEANDRO N., FERNANDO J.

• A New Hybrid Feature Subset Selection Framework Based on Binary Genetic Algorithm and Information Theory

  Citation: 51

  Authors: Alok Kumar, Pradeep, Manu

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