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논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
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- 건국대학교 지식콘텐츠연구소 International Journal of Knowledge Content Development & Technology International Journal of Knowledge Content Development & Technology Vol.10 No.4
- 발행연도
- 2020.12
- 수록면
- 29 - 46 (18page)
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The paper describes the quantitative and qualitative dimensions of artificial neural networks (ANN) in India in the global context. The study is based on research publications data (8260) as covered in the Scopus database during 1999-2018. ANN research in India registered 24.52% growth, averaged 11.95 citations per paper, and contributed 9.77% share to the global ANN research. ANN research is skewed as the top 10 countries account for 75.15% of global output. India ranks as the third most productive country in the world. The distribution of research by type of ANN networks reveals that Feed Forward Neural Network type accounted for the highest share (10.18% share), followed by Adaptive Weight Neural Network (5.38% share), Feed Backward Neural Network (2.54% share), etc. ANN research applications across subjects were the largest in medical science and environmental science (11.82% and 10.84% share respectively), followed by materials science, energy, chemical engineering and water resources (from 6.36% to 9.12%), etc. The Indian Institute of Technology, Kharagpur and the Indian Institute of Technology, Roorkee lead the country as the most productive organizations (with 289 and 264 papers). Besides, the Indian Institute of Technology, Kanpur (33.04 and 2.76) and Indian Institute of Technology, Madras (24.26 and 2.03) lead the country as the most impactful organizations in terms of citation per paper and relative citation index. P. Samui and T.N. Singh have been the most productive authors and G.P.S.Raghava (86.21 and 7.21) and K.P. Sudheer (84.88 and 7.1) have been the most impactful authors. Neurocomputing, International Journal of Applied Engineering Research and Applied Soft Computing topped the list of most productive journals.
목차
ABSTRACT
1. Introduction
2. Literature Review
3. Methodology
4. Results
5. Conclusion
참고문헌 (11)
참고문헌 신청
Amsaveni, N. / 2016 / Assessment of Bradford Law’s of Scattering to Neural Network Literature through Bibliometric Study / International Journal of Next Generation Library and Technologies 2(3):1~15
Claude, R. / 2004 / Bibliometric Overview of the Utilization of Artificial Neural Networks in Medicine and Biology / Scientometrics 59(1):117~130
Elprocus / Artificial Neural Networks (ANN) and Different Types
Kumar, S. / 2016 / Scientometric Study of Artificial Neural Networks Research in India / International Journal of Information Dissemination and Technology 6(S1):S16~20
Kumar, S / 2016 / An Evaluation of Author Productivity in Artificial Neural Networks Research in India during 1991-2014 / Annals of Library and Information Studies 63:126~131
Claude, R. / 2004 / Bibliometric Overview of the Utilization of Artificial Neural Networks in Medicine and Biology / Scientometrics 59(1):117~130
Elprocus / Artificial Neural Networks (ANN) and Different Types
Kumar, S. / 2016 / Scientometric Study of Artificial Neural Networks Research in India / International Journal of Information Dissemination and Technology 6(S1):S16~20
Kumar, S / 2016 / An Evaluation of Author Productivity in Artificial Neural Networks Research in India during 1991-2014 / Annals of Library and Information Studies 63:126~131
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UCI(KEPA) : I410-ECN-0101-2020-309-001101220