| Stage | Typical Duration | |-------|------------------| | | ~7–14 days (desk review) | | Peer review | ~2–4 months | | Final decision | ~3–5 months from submission | | Online first | ~2–4 weeks after acceptance |
The journal prioritizes research that addresses real-world problems through practical system building. Key areas of interest include: Neural Networks
The stock market is a sea of noise. Neural networks identify subtle trends and correlations in vast datasets, helping institutions predict market shifts and manage risk profiles more effectively. 4. Natural Language Processing (NLP)
According to LetPub user data, NCAA typically features a moderate to fast initial screening process. The time to first decision usually ranges between . Desk rejections often happen within the first two weeks, saving authors valuable time if the paper is deemed a poor fit. 2. Total Publication Timeline neural computing and applications letpub
Generally ranked in Q1 for Artificial Intelligence and Software. Impact Metrics: CiteScore (2025): 11.7.
: Intelligent control systems, real-time forecasting, automated diagnostics, and pattern recognition. Bibliometric Profile on LetPub
: Averages 3 to 5 months . The paper is typically assigned to 3 or more expert reviewers. | Stage | Typical Duration | |-------|------------------| |
The journal’s title is Neural Computing . Pure theoretical papers without real or simulated applications are often rejected. Include a section on: case study, benchmark comparison with state-of-the-art, or deployment scenario.
According to data listed on academic resources like LetPub, Neural Computing and Applications is widely recognized as a high-quality, reputable, and high-impact publication venue. What is Neural Computing and Applications (NCA)?
NCAA’s stated scope (via LetPub summary) is: Desk rejections often happen within the first two
Neural computing, also known as neural networks, is a subfield of artificial intelligence that mimics the structure and function of the human brain. It involves the use of artificial neural networks (ANNs) to analyze data, recognize patterns, and make decisions. ANNs are composed of interconnected nodes or "neurons" that process and transmit information, enabling the network to learn and adapt.
Include a link to code (GitHub, Zenodo) and detailed hyperparameters. Several LetPub reviewers complained that papers missing code or with ambiguous pseudo-code were asked for major revisions.