Journal of Intelligent and Fuzzy Systems

Aims & Scope

The purpose of the Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology is to foster advancements of knowledge and help disseminate results concerning recent applications and case studies in the areas of fuzzy logic, intelligent systems, and web-based applications among working professionals and professionals in education and research, covering a broad cross-section of technical disciplines.

The journal will publish original articles on current and potential applications, case studies, and education in intelligent systems, fuzzy systems, and web-based systems for engineering and other technical fields in science and technology.

The journal focuses on the disciplines of computer science, electrical engineering, manufacturing engineering, industrial engineering, chemical engineering, mechanical engineering, civil engineering, engineering management, bioengineering, and biomedical engineering.

The scope of the journal also includes developing technologies in mathematics, operations research, technology management, the hard and soft sciences, and technical, social and environmental issues.

View Aims & Scope

---

Metrics & Ranking

Impact Factor

Year	Value
2025	1
2024	1.70

SJR (SCImago Journal Rank)

Year	Value
2024	0.364

Quartile

Year	Value
2024	Q2

h-index

Year	Value
2024	89

Journal Rank

Year	Value
2024	14764

Journal Citation Indicator

Year	Value
2024	7753

---

---

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

---

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.

---

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.

• Fuzzy Model Identification Based on Cluster Estimation

  Citation: 1815

  Authors: Stephen L.

• Spherical fuzzy sets and spherical fuzzy TOPSIS method

  Citation: 687

  Authors: Fatma, Cengiz

• A multicriteria decision-making method using aggregation operators for simplified neutrosophic sets

  Citation: 469

  Authors: Jun

• Generation of Fuzzy Rules by Mountain Clustering

  Citation: 445

  Authors: Ronald R., Dimitar P.

• Image segmentation by generalized hierarchical fuzzy C-means algorithm

  Citation: 316

  Authors: Yuhui, Byeungwoo, Danhua, Q.M. Jonathan, Hui

• RETRACTED: Picture fuzzy aggregation operators and their application to multiple attribute decision making

  Citation: 312

  Authors: Guiwu

• Spherical fuzzy sets and their applications in multi-attribute decision making problems

  Citation: 308

  Authors: Shahzaib, Saleem, Tahir, Fazal, Tariq

• A numerical method for solving uncertain differential equations

  Citation: 294

  Authors: Kai, Xiaowei

• Linear Diophantine fuzzy set and its applications towards multi-attribute decision-making problems

  Citation: 293

  Authors: Muhammad, Masooma Raza

• Similarity measures between interval neutrosophic sets and their applications in multicriteria decision-making

  Citation: 275

  Authors: Jun

---