LetPub is a leading author-services platform that hosts a comprehensive journal performance database. It aggregates peer-reviewed data and direct feedback from scholars worldwide to give prospective authors an inside look at a journal's editorial behavior. Key Metrics Tracked on LetPub
A high CiteScore of 11.70 indicates that, on average, articles published in the journal are cited approximately 11-12 times each, reflecting a strong and active readership within the AI community. neural computing and applications letpub
Note: Always check LetPub or the Journal Citation Reports (JCR) for the most current metrics. LetPub is a leading author-services platform that hosts
: This stage can occasionally take several weeks if internal discrepancies emerge among reviewer scores, or if the associate editor requests additional opinions. Strategy for Success: Pre-submission Checklist Note: Always check LetPub or the Journal Citation
When assessing a target journal on the LetPub SCI Database , authors prioritize predictability, impact, and stability. The following structured data captures the baseline metrics for Neural Computing and Applications as recorded in recent tracking periods: Metric Parameter Current Status / Value Academic Significance Springer London / Nature High global visibility and institutional distribution. CiteScore 11.70 Steady multi-year growth in citation density per document. H-Index 111 High career-level impact for published authors. Annual Article Output ~1,091 papers Large capacity reduces desk-rejection bottlenecking. Self-Citation Rate Safely below the warning threshold; shields against risk. Primary Categories Computer Science: Artificial Intelligence Cross-indexed under Control Theory & Applications. Understanding the Editorial Scope of NCAA