Linear regression models have been developed to predict the trip generation for a neighbourhood during the specific time$-$of$-$day period $D$

as follows:

$T_h^{sh}=0\mathrm{.}12+0\mathrm{.}09(HHS)+0\mathrm{.}011(INC)-0\mathrm{.}15($ EMP $)$

$T_h^{re}=0\mathrm{.}04+0\mathrm{.}018(HHS)+0\mathrm{.}009(INC)+0\mathrm{.}16(NW)$

where

$T_h^{sh}=$ number of shopping trips in time$-$of$-$day period $D$ made by household type $h$

$T_h^{re}=$ number of social$/$recreational trips in time$-$of$-$day period $D$ made by household type $h$

HHS $=$ household size $($number of household members$)$

INC $=$ annual household income, in thousands of dollars

EMP$=$ employment in the household's neighbourhood, in hundreds

$NW=$ number of nonworking household members

This neighbourhood has $205$ retail employees and $700$ households. The households can be categorised into four types, with each type

having characteristics as follows:

Determine the number of shopping trips generated from this neighbourhood during time$-$of$-$day period $D.$

Please round your numeric calculation answer to the nearest whole number.