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h5 指数:110
h5 中位数:170

h5 指数是指在过去整整 5 年中所发表文章的 h 指数。h 指在 2018-2022 年间发表的 h 篇文章每篇至少都被引用过 h 次的最大值。隐藏

出版物的 h5 中位数，是指出版物的 h5 指数所涵盖的所有文章获得的引用次数的中位值。隐藏

#1 Nonlinear Science
#19 Physics & Mathematics

标题/作者	引用次数	年份
Analysis and forecast of COVID-19 spreading in China, Italy and France D Fanelli, F Piazza Chaos, Solitons & Fractals 134, 109761	1061	2020
Time series forecasting of COVID-19 transmission in Canada using LSTM networks VKR Chimmula, L Zhang Chaos, Solitons & Fractals 135, 109864	846	2020
Applications of machine learning and artificial intelligence for Covid-19 (SARS-CoV-2) pandemic: A review S Lalmuanawma, J Hussain, L Chhakchhuak Chaos, Solitons & Fractals 139, 110059	729	2020
Mathematical modeling of COVID-19 transmission dynamics with a case study of Wuhan F Ndaïrou, I Area, JJ Nieto, DFM Torres Chaos, Solitons & Fractals 135, 109846	632	2020
A SIR model assumption for the spread of COVID-19 in different communities I Cooper, A Mondal, CG Antonopoulos Chaos, Solitons & Fractals 139, 110057	618	2020
Application of deep learning for fast detection of COVID-19 in X-Rays using nCOVnet H Panwar, PK Gupta, MK Siddiqui, R Morales-Menendez, V Singh Chaos, Solitons & Fractals 138, 109944	544	2020
A new study on the mathematical modelling of human liver with Caputo–Fabrizio fractional derivative D Baleanu, A Jajarmi, H Mohammadi, S Rezapour Chaos, Solitons & Fractals 134, 109705	506	2020
Short-term forecasting COVID-19 cumulative confirmed cases: Perspectives for Brazil MHDM Ribeiro, RG da Silva, VC Mariani, L dos Santos Coelho Chaos, Solitons & Fractals 135, 109853	473	2020
Predictions for COVID-19 with deep learning models of LSTM, GRU and Bi-LSTM F Shahid, A Zameer, M Muneeb Chaos, Solitons & Fractals 140, 110212	452	2020
Deep learning methods for forecasting COVID-19 time-Series data: A Comparative study A Zeroual, F Harrou, A Dairi, Y Sun Chaos, Solitons & Fractals 140, 110121	420	2020
Modelling the spread of COVID-19 with new fractal-fractional operators: Can the lockdown save mankind before vaccination? A Atangana Chaos, Solitons & Fractals 136, 109860	411	2020
COVID-ABS: An agent-based model of COVID-19 epidemic to simulate health and economic effects of social distancing interventions PCL Silva, PVC Batista, HS Lima, MA Alves, FG Guimarães, RCP Silva Chaos, Solitons & Fractals 139, 110088	392	2020
Real-time forecasts and risk assessment of novel coronavirus (COVID-19) cases: A data-driven analysis T Chakraborty, I Ghosh Chaos, Solitons & Fractals 135, 109850	392	2020
Modeling and forecasting the COVID-19 pandemic in India K Sarkar, S Khajanchi, JJ Nieto Chaos, Solitons & Fractals 139, 110049	390	2020
A model based study on the dynamics of COVID-19: Prediction and control M Mandal, S Jana, SK Nandi, A Khatua, S Adak, TK Kar Chaos, Solitons & Fractals 136, 109889	346	2020
A deep learning and grad-CAM based color visualization approach for fast detection of COVID-19 cases using chest X-ray and CT-Scan images H Panwar, PK Gupta, MK Siddiqui, R Morales-Menendez, P Bhardwaj, ... Chaos, Solitons & Fractals 140, 110190	332	2020
Prediction and analysis of COVID-19 positive cases using deep learning models: A descriptive case study of India P Arora, H Kumar, BK Panigrahi Chaos, Solitons & Fractals 139, 110017	327	2020
A study of behaviour for immune and tumor cells in immunogenetic tumour model with non-singular fractional derivative B Ghanbari, S Kumar, R Kumar Chaos, Solitons & Fractals 133, 109619	315	2020
Fractional derivatives with no-index law property: Application to chaos and statistics A Atangana, JF Gómez-Aguilar Chaos, Solitons & Fractals 114, 516-535	310	2018
Prediction of epidemic trends in COVID-19 with logistic model and machine learning technics P Wang, X Zheng, J Li, B Zhu Chaos, Solitons & Fractals 139, 110058	306	2020

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