Neural Computing And Applications Letpub
Here is the detailed information regarding Neural Computing and Applications from LetPub (a popular journal evaluation and submission system resource in China).
2-Year Impact Factor (2024/2025): Approximately 3.98 to 4.5. Real-time Impact Factor (Jan 2026): 4.7. neural computing and applications letpub
5. Common reasons for desk rejection
- Insufficient novelty or incremental contribution.
- Poor experimental rigor (missing baselines or unclear metrics).
- Lack of reproducibility details.
- English language clarity issues.
- Out‑of‑scope content or weak application relevance.
Impact Factor: The 2-year impact is approximately 3.986, with real-time estimates for 2026 trending around 4.7. Here is the detailed information regarding Neural Computing
3. Technical and presentation best practices
- Reproducibility: provide dataset sources, hyperparameters, random seeds, code link or supplementary material.
- Baselines: compare with strong, recent baselines and include ablation studies.
- Evaluation: use appropriate metrics, cross‑validation where applicable, and statistical tests for improvements.
- Figures & Tables: high resolution, self‑contained captions, clear axis labels.
- Clarity: concise notation, consistent symbols, and a table of key notation if dense.
- Ethics & Safety: discuss dataset bias, potential misuse, and privacy when relevant.
: Case histories in forecasting, diagnostics, and control systems. Key Metrics (2024-2026 Data) Journal Quartile (Top-tier in its field) Acceptance Rate Insufficient novelty or incremental contribution
Acceptance Rate: Reported around 50% by contributors on LetPub. Core Scope and Topics