Comparative Study on Predictive Mathematical Models for Risk Assessment of nCOVID-19 Pandemic in India

2021 ◽  
pp. 393-404
Author(s):  
Swarnava Biswas ◽  
Anoop Kumar Prasad ◽  
Debajit Sen ◽  
Dinesh Bhatia ◽  
Moumita Mukherjee
Keyword(s):  
Risk Assessment ◽  
Comparative Study ◽  
Mathematical Models

scholarly journals Risk assessment of the cities of Estonia and the UK: comparative study

2008 ◽  
Author(s):  
A. Tammepuu ◽  
K. Sepp ◽  
R. Paasoja ◽  
V. Kuusemets
Keyword(s):  
Risk Assessment ◽  
Comparative Study ◽  
The Uk

How to model the impact of climate change on vector-borne diseases?

2021 ◽  
pp. 26-31
Author(s):  
Cyril Caminade
Keyword(s):  
Climate Change ◽  
Risk Assessment ◽  
Mathematical Models ◽  
Future Climate ◽  
Future Climate Change ◽  
Climate Change Risk ◽  
Vector Borne Diseases ◽  
Impact Of Climate Change ◽  
Vector Borne ◽  
The Impact

Abstract This expert opinion provides an overview of mathematical models that have been used to assess the impact of climate change on ticks and tick-borne diseases, ways forward in terms of improving models for the recent context and broad guidelines for conducting future climate change risk assessment.

scholarly journals COMPARATIVE STUDY OF DIFFERENT MODELS FOR CALCULATION OF DNI

2018 ◽  
Vol 17 (2) ◽  
pp. 28
Author(s):  
G. S. Lima ◽  
A. O. Souza ◽  
G. I. Medina T.
Keyword(s):  
Experimental Data ◽  
Mathematical Model ◽  
Comparative Study ◽  
Mathematical Models ◽  
Environmental Variables ◽  
Solar Power ◽  
Measuring Instruments ◽  
Concentrating Solar Power ◽  
Direct Normal Irradiance

For prospecting or design of Concentrating Solar Power (CSP) systems it is necessary to know the distribution of the Direct Normal Irradiance (DNI) of the region. However, due to the recurring operational problems of measuring instruments, the use of mathematical models estimating the local DNI can be a very useful tool. The objective of this work is to construct a mathematical model that is used in the calculation of the DNI using experimental data provided by the Laboratory of Tropical Environmental Variables (LAVAT/INPE). This model was compared with other mathematical models already present in the literature. The consideration of clean-sky was used, that is, the effects of cloudiness, among others, were neglected.

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