Table 2 Parametric settings of MPV model (3),

From: Poisson random measure noise-induced coherence in epidemiological priors informed deep neural networks to identify the intensity of virus dynamics

Parameter

Case I

Case II

Case III

\(\omega _{\textrm{h}}\)

0.29

0.32

0.32

\(\omega _{\textrm{r}}\)

0.20

0.28

0.28

\(\eta _{1}\)

0.30

0.40

0.30

\(\eta _{2}\)

0.30

0.35

0.45

\(\eta _{3}\)

0.30

0.40

0.70

\(\psi _{1}\)

0.20

0.18

0.18

\(\psi _{2}\)

0.10

0.08

0.08

\(\psi _{3}\)

0.20

0.18

0.18

\(\phi\)

0.20

0.25

0.25

\(\lambda\)

0.05

0.03

0.03

\(\gamma\)

0.10

0.12

0.12

\(\mu _{\textrm{h}}\)

0.01

0.0008

0.0008

\(\mu _{\textrm{r}}\)

0.01

0.007

0.007

\(\rho _{\textrm{r}}\)

0.05

0.04

0.04

\(\rho _{\textrm{h}}\)

0.20

0.12

0.12

\({S}_{\textrm{h}}(0)\)

0.1

0.2

0.3

\({E}_{\textrm{h}}(0)\)

0.2

0.1

0.2

\({I}_{\textrm{h}}(0)\)

0.3

0.4

0.1

\({Q}_{\textrm{h}}(0)\)

0.4

0.3

0.6

\({R}_{\textrm{h}}(0)\)

0.5

0.6

0.5

\({S}_{\textrm{r}}(0)\)

0.6

0.5

0.4

\({E}_{\textrm{r}}(0)\)

0.7

0.8

0.8

\({I}_{\textrm{r}}(0)\)

0.8

0.7

0.7

...

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...

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