Neural Network World - Impact Factor

Neural Network World - Czech Technical University | 2024 Impact Factor:1.02 | Cite Score:2.1 | Q4

Impact Factor and Journal Rank of Neural Network World

About: The Cognitive Processing Journal is an international, peer-reviewed journal that focuses on the interdisciplinary study of cognition. It aims to bring together researchers from various fields to share and advance understanding in areas related to cognitive processes.
Impact and Significance
The Cognitive Processing Journal is significant for several reasons:
Interdisciplinary Approach: It fosters collaboration and knowledge sharing across various disciplines, including psychology, neuroscience, artificial intelligence, linguistics, and philosophy.
Broad Coverage: The journal covers a wide array of cognitive topics, making it a comprehensive resource for researchers in the field.
High-Quality Research: It maintains rigorous peer-review standards to ensure the publication of high-quality and impactful research.
Global Reach: The journal attracts contributions from researchers around the world, promoting global perspectives and advancements in cognitive science.
Educational Resource: It serves as a valuable resource for students, educators, and professionals seeking to stay updated on the latest research in cognitive processing.
Types of Articles Accepted
The Cognitive Processing Journal accepts the following types of submissions:
Research Articles: Detailed studies presenting original research findings.
Review Articles: Comprehensive reviews of the current state of research on specific topics in cognitive science.
Theoretical Papers: Articles that propose new theories or models in cognitive processing.
Short Communications: Brief reports on novel findings or innovative research ideas.
Opinion Pieces: Expert opinions and perspectives on current trends and future directions in cognitive science.

Journal Home: Journal Homepage

Editor-in-Chief: Petr Bouchner

Scope: Neural Network World is a peer-reviewed journal that publishes original research articles, reviews, and theoretical papers on neural networks and related artificial intelligence technologies. The journal covers a wide range of topics within neural networks and related areas, including but not limited to:
Artificial Neural Networks: Theoretical foundations, architectures, and algorithms for artificial neural networks.
Deep Learning: Advances in deep learning techniques, models, and applications.
Machine Learning: Research on machine learning algorithms, including supervised, unsupervised, and reinforcement learning.
Pattern Recognition: Techniques and applications for recognizing patterns in data using neural networks.
Neurocomputing: The design and implementation of computational systems inspired by the brain.
Biological Neural Networks: Studies on the modeling and simulation of biological neural networks.
Evolutionary Computation: Research on evolutionary algorithms and their applications in neural network optimization.
Fuzzy Logic: Integration of fuzzy logic with neural networks and applications in intelligent systems.
Applications of Neural Networks: Real-world applications of neural networks in various domains such as robotics, healthcare, finance, and image processing.
Hybrid Systems: Research on systems that combine neural networks with other computational techniques, such as genetic algorithms and expert systems.