Neural Computing and Applications

Aims & Scope

Neural Computing & Applications is an international journal which publishes original research and other information in the field of practical applications of neural computing and related techniques such as genetic algorithms, fuzzy logic and neuro-fuzzy systems.

All items relevant to building practical systems are within its scope, including but not limited to: -adaptive computing- algorithms- applicable neural networks theory- applied statistics- architectures- artificial intelligence- benchmarks- case histories of innovative applications- fuzzy logic- genetic algorithms- hardware implementations- hybrid intelligent systems- intelligent agents- intelligent control systems- intelligent diagnostics- intelligent forecasting- machine learning- neural networks- neuro-fuzzy systems- pattern recognition- performance measures- self-learning systems- software simulations- supervised and unsupervised learning methods- system engineering and integration.

Featured contributions fall into several categories: Original Articles, Review Articles, Book Reviews and Announcements.

View Aims & Scope

---

Metrics & Ranking

SJR (SCImago Journal Rank)

Year	Value
2024	1.102

Quartile

Year	Value
2024	Q1

h-index

Year	Value
2024	146

Impact Factor

Year	Value
2024	4.50

Journal Rank

Year	Value
2024	4124

Journal Citation Indicator

Year	Value
2024	26087

---

---

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, 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.

• Multi-Verse Optimizer: a nature-inspired algorithm for global optimization

  Citation: 2469

  Authors: Seyedali, Seyed Mohammad, Abdolreza

• Dragonfly algorithm: a new meta-heuristic optimization technique for solving single-objective, discrete, and multi-objective problems

  Citation: 2306

  Authors: Seyedali

• A review of feature selection methods based on mutual information

  Citation: 946

  Authors: Jorge R., Pablo A.

• Cuckoo search: recent advances and applications

  Citation: 891

  Authors: Xin-She, Suash

• Grey wolf optimizer: a review of recent variants and applications

  Citation: 869

  Authors: Hossam, Ibrahim, Mohammed Azmi, Seyedali

• Monarch butterfly optimization

  Citation: 812

  Authors: Gai-Ge, Suash, Zhihua

• An approach toward decision-making and medical diagnosis problems using the concept of spherical fuzzy sets

  Citation: 734

  Authors: Tahir, Kifayat, Qaisar, Naeem

• A survey of multi-view machine learning

  Citation: 688

  Authors: Shiliang

• A CNN–LSTM model for gold price time-series forecasting

  Citation: 640

  Authors: Ioannis E., Emmanuel, Panagiotis

• Pattern classification with missing data: a review

  Citation: 604

  Authors: Pedro J., José-Luis, Aníbal R.

---