Neural Computing And Applications Letpub May 2026

Neural Computing and Applications LetPub: A Comprehensive Guide for Researchers

In the rapidly evolving landscape of artificial intelligence and machine learning, selecting the right journal for your research is as critical as the research itself. For scholars working on neural networks, deep learning architectures, and real-world AI applications, Neural Computing and Applications (NCAA) stands as a prominent hybrid journal. When combined with the resource LetPub, researchers gain a powerful toolkit for manuscript preparation, submission, and acceptance.

This article provides an exhaustive analysis of Neural Computing and Applications through the lens of LetPub data—covering impact factors, review timelines, acceptance rates, and strategic tips for publication.

2. Acceptance Rate Insights

Official Springer pages rarely state acceptance rates. However, synthesized LetPub user data suggests:

This makes NCAA more selective than lower-tier IEEE Access but slightly less competitive than Neurocomputing or IEEE TNNLS. neural computing and applications letpub

6. How LetPub can help (services summary)

Introduction

Neural computing refers to computational paradigms inspired by biological neural systems, spanning artificial neural networks (ANNs), spiking neural networks (SNNs), neuromorphic hardware, and related learning algorithms. "Neural Computing and Applications" is a journal title; LetPub is a scientific services platform that helps authors with manuscript preparation, journal selection, submission, and publication support. This examination evaluates the field of neural computing and applications with attention to research themes, methodological advances, application domains, evaluation criteria for high‑quality manuscripts, and practical guidance for authors using LetPub-like services to prepare submissions.

2. Reviewer Quality is High

Unlike some predatory or borderline journals, NCAA reviewers are generally experts in neural networks. Comments are detailed and constructive. One LetPub user wrote: “Two reviewers, each gave 10+ specific comments on methodology and experiments. Improved my paper significantly.”

LetPub’s Data Snapshot: Neural Computing and Applications

Based on the latest LetPub entry (2024–2025 data), here is the critical information: This makes NCAA more selective than lower-tier IEEE

| Metric | Value | |--------|-------| | Publisher | Springer London | | ISSN | 0941-0643 (print), 1433-3058 (electronic) | | 2023 Impact Factor | 5.6 (approx., check LetPub for real-time update) | | 5-Year Impact Factor | 5.2 | | CiteScore | 9.1 | | Review Speed (User-reported) | 4–6 months (first decision) | | Acceptance Rate | ~25% (highly competitive) | | Open Access Option | Yes (Hybrid) | | APC for OA | $3,190 (as of 2025) | | Frequency | Monthly (12 issues/year) |

Note: Impact factors change annually. LetPub updates this data after each JCR release. Always check the live entry.

Title

A concise overview of "Neural Computing and Applications" — publishing with LetPub guidance Applied Soft Computing .

How to Verify Neural Computing and Applications on LetPub (2025 Update)

  1. Go to letpub.com.cn (or the English mirror).
  2. Search “Neural Computing and Applications” in the journal finder.
  3. Look for the blue shield icon – indicates verified journal (non-predatory).
  4. Check the latest user comments – sort by date to avoid obsolete information.
  5. Compare with similar journals: Neurocomputing, Neural Networks, Applied Soft Computing.

5. Submission & Publication Fees

| Model | Cost | |-------|------| | Traditional subscription | No fee for authors (free to publish) | | Open Access (OA) | ~$2790–3290 USD (APC, may vary) |

Check Springer’s latest APC – LetPub usually mirrors this.