Artificial Intelligence (AI) refers to the simulation of human intelligence in machine-driven systems that are programmed to think, learn from data, and perform tasks like sensing, comprehending languages, automating decisions and predictions. The advent of AI through machine learning has transformed numerous fields, especially engineering, by enhancing productivity, quality and safety. As AI augmentations continue rising across aerospace, mechanical, civil, electrical and software engineering verticals, so does high-impact research into real-world applications.
One prestigious journal publishing pioneering AI scholarship for engineers is Elsevier’s monthly “Engineering Applications of Artificial Intelligence” (EAAI). With a 2022 impact factor of 7.8 and a 95th percentile rank under the Engineering category, EAAI has solidified itself as a world-leading venue for applied AI contributions. This article reviews metrics reflecting EAAI’s influence and importance for the engineering community.
What is Impact Factor?
The journal impact factor was conceived in 1975 to evaluate the citation frequency of a journal’s articles as a proxy for its reach and significance in scientific circles. It quantifies the average number of citations received per article published in that journal across a preceding 2-year period.
For instance, EAAI’s 2022 impact factor of 7.8 indicates its articles published in 2020 and 2021 received on average 7.8 citations during 2022. Higher impact factors signal journals contain cutting edge research deemed useful by more scientists that cite them in their own work. As citation counts keep accumulating annually post-publication, impact factors reflect a snapshot of citation rates rather than lifetime article performance.
While critiqued for variability across disciplines, impact factor offers a standardized benchmark to compare journals of similar scopes using objective citation data from scholarly databases like Web of Science and Scopus. It holds more accuracy for journals focused on specialized research areas with controlled article volumes. Overall, despite limitations, it generates valuable insights into journal quality based on collective readership data rather than subjective perceptions.
EAAI Journal
First published in 1987 under founding editor Dr. Alice Smith from The Aerospace Corporation, EAAI rapidly expanded as an interdisciplinary monthly journal channeling advancements in applied AI research to solve complex engineering problems. Now led by Editor-in-Chief Dr. Nikola Kasabov from Auckland University of Technology, the journal solicits original contributions elucidating contemporary and emerging AI models, algorithms, tools and technologies demonstrating validated utility across all domains of engineering application.
Owing to rigorous peer review by global domain experts and backing by leading publisher Elsevier, EAAI has evolved into a premier source for knowledge exchange between artificial intelligence and engineering research communities. Its open access options coupled with high readership further enable rapid transfer of AI innovations into global practice to accelerate solutions engineering.
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EAAI Impact Factor
Current Impact Factor: According to the Scimago Journal Rankings, EAAI attained an impact factor of 7.8 as of 2022, calculated using 2021 citation data. This marks steady growth from 1.9 in 2012 to its all-time high this year, positioning it in the 95th percentile within its field.
The table below comparatively showcases EAAI’s leadership against category-relevant journals regarding impact.
| Journal Name | Impact Factor | Rank by Impact Factor |
|---|---|---|
| EAAI | 7.8 | 21 of 177 Journals (Engineering) |
| IEEE-TECI | 6.3 | 34 of 177 |
| Neurocomputing | 5.6 | 43 of 177 |
Such high citation rates highlight EAAI’s success as an authoritative forum showcasing AI advances with relevance for engineers globally across sectors.
Significance of EAAI Impact Factor
EAAI’s soaring 2022 journal impact factor directly signals its articles entail pioneering AI engineering insights that stimulate, influence and guide quality research worldwide. It signifies the journal’s manuscripts comprehensively capture state-of-the-art innovations in analysis, modeling, algorithm design, tools and implications across the applied AI landscape engineers operate in.
The high average citations articles receive yearly after publication indicate EAAI successfully publishes cutting-edge, timely AI research highly regarded by the engineering community. Global accessibility further multiplied its influence. For authors, publishing high-impact research in EAAI amplifies manuscript visibility to wide subscribed audiences, accelerating uptake. Rigorous peer review builds author credibility as pioneering AI engineering experts. Overall, EAAI enables scholars to contribute directly to transforming engineering systems and solutions through impactful, applied AI research communicated worldwide.
Conclusion
EAAI has cemented itself as a premier journal for disseminating cutting-edge artificial intelligence advancements solving complex challenges across every engineering domain. With a 2022 impact factor of 7.8, EAAI ranks among top AI journals globally, signifying its published research stimulates substantial yearly citations and drives progress worldwide.
Several key points underpin EAAI’s soaring impact:
- High citation rates highlight the engineering community’s reliance on EAAI to source pioneering applied AI innovations guiding systems augmentation across sectors.
- Top-tier peer review processes underscore published manuscripts’ rigorous quality, positioning EAAI as a trusted hub for state-of-the-art AI modeling, algorithms, tools, and implications research.
- Open access options coupled with a monthly publication model enable EAAI to achieve wide readership and amplify research visibility, uptake and influence globally at an accelerated pace aligned with AI’s speed of advancement.
In summary, EAAI’s world-leading impact factor signals its effectiveness as the premier destination for sharing and accessing groundbreaking artificial intelligence research bettering engineering solutions to advance industry and society worldwide. Researchers aiming to publish work transforming global engineering practice via AI should target EAAI.