OOIR: Observatory of International Research

Papers

(The H4-Index of Chaos Solitons & Fractals is 91. The table below lists those papers that are above that threshold based on CrossRef citation counts [max. 250 papers]. The publications cover those that have been published in the past four years, i.e., from 2020-05-01 to 2024-05-01.)

Article	Citations
Analysis and forecast of COVID-19 spreading in China, Italy and France	709
Time series forecasting of COVID-19 transmission in Canada using LSTM networks	671
A new study on the mathematical modelling of human liver with Caputo–Fabrizio fractional derivative	550
Applications of machine learning and artificial intelligence for Covid-19 (SARS-CoV-2) pandemic: A review	543
A SIR model assumption for the spread of COVID-19 in different communities	464
Application of deep learning for fast detection of COVID-19 in X-Rays using nCOVnet	429
Predictions for COVID-19 with deep learning models of LSTM, GRU and Bi-LSTM	427
Mathematical modeling of COVID-19 transmission dynamics with a case study of Wuhan	426
Modelling the spread of COVID-19 with new fractal-fractional operators: Can the lockdown save mankind before vaccination?	384
Modeling and forecasting the COVID-19 pandemic in India	330
Short-term forecasting COVID-19 cumulative confirmed cases: Perspectives for Brazil	327
Deep learning methods for forecasting COVID-19 time-Series data: A Comparative study	321
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	303
Recognition of COVID-19 disease from X-ray images by hybrid model consisting of 2D curvelet transform, chaotic salp swarm algorithm and deep learning technique	284
COVID-ABS: An agent-based model of COVID-19 epidemic to simulate health and economic effects of social distancing interventions	278
CoroDet: A deep learning based classification for COVID-19 detection using chest X-ray images	278
Real-time forecasts and risk assessment of novel coronavirus (COVID-19) cases: A data-driven analysis	275
A theoretical study of the Caputo–Fabrizio fractional modeling for hearing loss due to Mumps virus with optimal control	270
A model based study on the dynamics of COVID-19: Prediction and control	265
Prediction and analysis of COVID-19 positive cases using deep learning models: A descriptive case study of India	246
A mathematical model for COVID-19 transmission by using the Caputo fractional derivative	242
Convolutional capsnet: A novel artificial neural network approach to detect COVID-19 disease from X-ray images using capsule networks	238
Stability analysis and numerical simulation of SEIR model for pandemic COVID-19 spread in Indonesia	229
Chaotic behaviour of fractional predator-prey dynamical system	222
Prediction of epidemic trends in COVID-19 with logistic model and machine learning technics	216

Comparison of deep learning approaches to predict COVID-19 infection	208
A mathematical model for COVID-19 transmission dynamics with a case study of India	191
Time series forecasting of Covid-19 using deep learning models: India-USA comparative case study	186
Diagnosis and detection of infected tissue of COVID-19 patients based on lung x-ray image using convolutional neural network approaches	178
A new study of unreported cases of 2019-nCOV epidemic outbreaks	172
Comparative analysis and forecasting of COVID-19 cases in various European countries with ARIMA, NARNN and LSTM approaches	171
Modeling and forecasting of epidemic spreading: The case of Covid-19 and beyond	169
Modeling the impact of non-pharmaceutical interventions on the dynamics of novel coronavirus with optimal control analysis with a case study	157
A new adaptive synchronization and hyperchaos control of a biological snap oscillator	154
Analysis of a mathematical model for COVID-19 population dynamics in Lagos, Nigeria	153
CVDNet: A novel deep learning architecture for detection of coronavirus (Covid-19) from chest x-ray images	147
Association between weather data and COVID-19 pandemic predicting mortality rate: Machine learning approaches	146
A chaos study of tumor and effector cells in fractional tumor-immune model for cancer treatment	145
On a comprehensive model of the novel coronavirus (COVID-19) under Mittag-Leffler derivative	143
Analytical mathematical approaches for the double-chain model of DNA by a novel computational technique	143
New concept in calculus: Piecewise differential and integral operators	140
Time Series Analysis and Forecast of the COVID-19 Pandemic in India using Genetic Programming	140
Estimation of COVID-19 dynamics “on a back-of-envelope”: Does the simplest SIR model provide quantitative parameters and predictions?	140
Assessment of lockdown effect in some states and overall India: A predictive mathematical study on COVID-19 outbreak	140
Global stability and cost-effectiveness analysis of COVID-19 considering the impact of the environment: using data from Ghana	138
Chaotic dynamics of a fractional order HIV-1 model involving AIDS-related cancer cells	135
Novel trial functions and rogue waves of generalized breaking soliton equation via bilinear neural network method	134
The impact of COVID-19 pandemic upon stability and sequential irregularity of equity and cryptocurrency markets	133
Role of intelligent computing in COVID-19 prognosis: A state-of-the-art review	131
Fractional order mathematical modeling of COVID-19 transmission	131
Global dynamics of a fractional order model for the transmission of HIV epidemic with optimal control	129
A discrete memristor model and its application in Hénon map	128
Statistical analysis of forecasting COVID-19 for upcoming month in Pakistan	127
Semi-analytical study of Pine Wilt Disease model with convex rate under Caputo–Febrizio fractional order derivative	126
Predicting turning point, duration and attack rate of COVID-19 outbreaks in major Western countries	125
Applications of artificial intelligence in battling against covid-19: A literature review	120
Analysis on novel coronavirus (COVID-19) using machine learning methods	117
Neural network powered COVID-19 spread forecasting model	116
A fractional-order chaotic system with hidden attractor and self-excited attractor and its DSP implementation	116
Analysis of Spatial Spread Relationships of Coronavirus (COVID-19) Pandemic in the World using Self Organizing Maps	115
A python based support vector regression model for prediction of COVID19 cases in India	113
Spatio-temporal estimation of the daily cases of COVID-19 in worldwide using random forest machine learning algorithm	110
Robustness of LSTM neural networks for multi-step forecasting of chaotic time series	110
Time series prediction for the epidemic trends of COVID-19 using the improved LSTM deep learning method: Case studies in Russia, Peru and Iran	110
Mathematical analysis of a fractional differential model of HBV infection with antibody immune response	110
The effect of market confidence on a financial system from the perspective of fractional calculus: Numerical investigation and circuit realization	108
Double image encryption algorithm based on neural network and chaos	108
Lie symmetry analysis for obtaining the abundant exact solutions, optimal system and dynamics of solitons for a higher-dimensional Fokas equation	107
SIR epidemic model with Mittag–Leffler fractional derivative	107
Shallow water in an open sea or a wide channel: Auto- and non-auto-Bäcklund transformations with solitons for a generalized (2+1)-dimensional dispersive long-wave system	107
Study of multiple lump and rogue waves to the generalized unstable space time fractional nonlinear Schrödinger equation	105
Forecasting of COVID-19 using deep layer Recurrent Neural Networks (RNNs) with Gated Recurrent Units (GRUs) and Long Short-Term Memory (LSTM) cells	105
Modeling and prediction of COVID-19 in Mexico applying mathematical and computational models	105
New approach for the model describing the deathly disease in pregnant women using Mittag-Leffler function	105
Analysis of the impact of COVID-19 on the correlations between crude oil and agricultural futures	104

Prediction of COVID-19 confirmed cases combining deep learning methods and Bayesian optimization	104
Stochastic resonance in a metal-oxide memristive device	103
Novel fractional order SIDARTHE mathematical model of COVID-19 pandemic	102
Mathematical analysis of spread and control of the novel corona virus (COVID-19) in China	102
Fractal-fractional differentiation for the modeling and mathematical analysis of nonlinear diarrhea transmission dynamics under the use of real data	102
Lie group analysis, solitons, self-adjointness and conservation laws of the modified Zakharov-Kuznetsov equation in an electron-positron-ion magnetoplasma	99
Analysis of fractional blood alcohol model with composite fractional derivative	97
Analytical and numerical study of the DNA dynamics arising in oscillator-chain of Peyrard-Bishop model	97
Development of new hybrid model of discrete wavelet decomposition and autoregressive integrated moving average (ARIMA) models in application to one month forecast the casualties cases of COVID-19	95
Forecasting of COVID-19 time series for countries in the world based on a hybrid approach combining the fractal dimension and fuzzy logic	94
Fractional Hausdorff grey model and its properties	93
Hidden coexisting hyperchaos of new memristive neuron model and its application in image encryption	93
An efficient computational approach for a fractional-order biological population model with carrying capacity	92
Analysis of spatiotemporal characteristics of big data on social media sentiment with COVID-19 epidemic topics	92
Optimal policies for control of the novel coronavirus disease (COVID-19) outbreak	92
Automatic distinction between COVID-19 and common pneumonia using multi-scale convolutional neural network on chest CT scans	91
Perturbation of chirped localized waves in a dual-power law nonlinear medium	91