activity
20112026
most citedAnalysis of the COVID-19 pandemic by SIR model and machine learning technics for forecasting

47 citations · 82 across the 13 of their papers we have counts for

collaborators
Showing 2020Show all

5 papers · 1 filter

q-bio.PE2020★ 1 cited

Analysis of COVID-19 evolution in Senegal: impact of health care capacity

Mouhamed M. Fall, Babacar M. Ndiaye, Ousmane Seydi +1

We consider a compartmental model from which we incorporate a time-dependent health care capacity having a logistic growth. This allows us to take into account the Senegalese autho…

math.AP2020

Existence and uniqueness of solution for semi linear conservation laws with velocity field in

S. Kane, S. F. Samb, D. Seck

In this paper we extend results obtained in [3] and [5]. By considering a semi linear conservation law with velocity in , we prove by fixed point arguments existence and…

q-bio.PE2020★ 8 cited

Visualization and machine learning for forecasting of COVID-19 in Senegal

Babacar Mbaye Ndiaye, Mouhamadou A. M. T. Balde, Diaraf Seck

In this article, we give visualization and different machine learning technics for two weeks and 40 days ahead forecast based on public data. On July 15, 2020, Senegal reopened its…

q-bio.PE2020★ 26 cited

Comparative prediction of confirmed cases with COVID-19 pandemic by machine learning, deterministic and stochastic SIR models

Babacar Mbaye Ndiaye, Lena Tendeng, Diaraf Seck

In this paper, we propose a machine learning technics and SIR models (deterministic and stochastic cases) with numerical approximations to predict the number of cases infected with…

q-bio.PE2020★ 47 cited

Analysis of the COVID-19 pandemic by SIR model and machine learning technics for forecasting

Babacar Mbaye Ndiaye, Lena Tendeng, Diaraf Seck

This work is a trial in which we propose SIR model and machine learning tools to analyze the coronavirus pandemic in the real world. Based on the public data from \cite{datahub}, w…