Research graph
References from Analysis of learning curves in predictive modeling using exponential curve fitting with an asymptotic approach. Local targets link to admitted publications; unresolved targets remain external evidence.
Estimation of COVID-19 prevalence in Italy, Spain, and France
10.1016/j.scitotenv.2020.138817 · 2020 · External reference
Mathematical parameters of the COVID-19 epidemic in Brazil and evaluation of the impact of different public health measures
10.3390/biology9080220 · 2020 · External reference
Characteristics of scientific articles on COVID-19 published during the initial 3 months of the pandemic.
10.1007/s11192-020-03632-0 · 2020 · External reference
A non-central beta model to forecast and evaluate pandemics time series.
10.1016/j.chaos.2020.110211 · 2020 · External reference
Forecasting Covid-19 dynamics in Brazil: a data driven approach
10.3390/ijerph17145115 · 2020 · External reference
Short-term forecasting COVID-19 cumulative confirmed cases: Perspectives for Brazil.
10.1016/j.chaos.2020.109853 · 2020 · External reference
Stochastic modelling for predicting COVID-19 prevalence in East Africa Countries
2020 · External reference
Understanding the temporal evolution of COVID-19 research through machine learning and natural language processing.
10.1007/s11192-020-03744-7 · 2021 · External reference
Scenario prediction of public health emergencies using infectious disease dynamics model and dynamic Bayes.
10.1016/j.future.2021.09.028 · 2022 · External reference
Statistical assessment of the learning curves of health technologies.
10.3310/hta5120 · 2001 · External reference
Statistical explorations and univariate timeseries analysis on covid-19 datasets to understand the trend of disease spreading and death.
10.3390/s20113089 · 2020 · External reference
Forecasting Brazilian and American COVID-19 cases based on artificial intelligence coupled with climatic exogenous variables
10.1016/j.chaos.2020.110027 · 2020 · External reference
Generated time-series prediction data of COVID-19′ s daily infections in Brazil by using recurrent neural networks
10.1016/j.dib.2020.106175 · 2020 · External reference
Assessment of impact of relaxation in lockdown and forecast of preparation for combating COVID-19 pandemic in India using Group Method of Data Handling.
10.1016/j.chaos.2020.110191 · 2020 · External reference
Evolutionary modelling of the COVID-19 pandemic in fifteen most affected countries.
10.1016/j.chaos.2020.110118 · 2020 · External reference
Predicting the evolution of the COVID-19 epidemic with the A-SIR model: Lombardy, Italy and Sao Paulo state, Brazil.
10.1016/j.physd.2020.132693 · 2020 · External reference
Constructing diverse classifier ensembles using artificial training examples
2003 · External reference
Estimating dataset size requirements for classifying DNA microarray data
10.1089/106652703321825928 · 2003 · External reference
Unresolved reference
2010 · External reference
Predicting sample size required for classification performance.
10.1186/1472-6947-12-8 · 2012 · External reference
Unresolved reference
2015 · External reference
The coefficient of determination R-squared is more informative than SMAPE, MAE, MAPE, MSE and RMSE in regression analysis evaluation
10.7717/peerj-cs.623 · 2021 · External reference
Forecasting energy consumption demand of customers in smart grid using Temporal Fusion Transformer (TFT).
10.1016/j.rineng.2023.100888 · 2023 · External reference
Comparative analysis and forecasting of COVID-19 cases in various European countries with ARIMA, NARNN and LSTM approaches.
10.1016/j.chaos.2020.110015 · 2020 · External reference
Unresolved reference
1978 · External reference
Comparison of adaptive neuro-fuzzy inference systems (ANFIS) and support vector regression (SVR) for data-driven modelling of aerobic granular sludge reactors.
10.1016/j.jece.2020.103742 · 2020 · External reference
A new mathematical modeling of the COVID-19 pandemic including the vaccination campaign
10.4236/ojmsi.2021.93020 · 2021 · External reference
Fractional order modelling of omicron SARS-CoV-2 variant containing heart attack effect using real data from the United Kingdom
10.1016/j.chaos.2022.111954 · 2022 · External reference
Modeling and Forecasting for the number of cases of the COVID-19 pandemic with the Curve Estimation Models, the Box-Jenkins and Exponential Smoothing Method.
2020 · External reference
Learning curves: Asymptotic values and rate of convergence
1994 · External reference
Selective sampling for approximate clustering of very large data sets
10.1002/int.20268 · 2008 · External reference
Bandwidth choice for average derivative estimation
1992 · External reference
How sensitive are average derivatives?
10.1016/0304-4076(93)90112-i · 1993 · External reference
Investigating smooth multiple regression by the method of average derivatives
1989 · External reference
An account of the herring investigations conducted at Plymouth during the years from 1924 to 1933
10.1017/s0025315400055910 · 1933 · External reference
A new graphic method of describing the growth of animals
10.2307/1538217 · 1946 · External reference
Unresolved reference
2021 · External reference
Unresolved reference
2021 · External reference
Research on COVID-19 Based on ARIMA Model—Taking Hubei, China as an example to see the epidemic in Italy.
10.1016/j.jiph.2020.06.019 · 2020 · External reference
Composite Monte Carlo decision making under high uncertainty of novel coronavirus epidemic using hybridized deep learning and fuzzy rule induction.
10.1016/j.asoc.2020.106282 · 2020 · External reference
Analysis of a probabilistic model of redundancy in unsupervised information extraction.
10.1016/j.artint.2010.04.024 · 2010 · External reference
Safe, learning-based MPC for highway driving under lane-change uncertainty: A distributionally robust approach.
10.1016/j.artint.2023.103920 · 2023 · External reference
A Bayesian approach to (online) transfer learning: Theory and algorithms.
10.1016/j.artint.2023.103991 · 2023 · External reference
