  We present a sample of 254,882 luminous red giant branch (LRGB) stars
selected from the APOGEE and LAMOST surveys. By combining photometric and
astrometric information from the 2MASS and Gaia surveys, the precise distances
of the sample stars are determined by a supervised machine learning algorithm:
the gradient boosted decision trees. To test the accuracy of the derived
distances, member stars of globular clusters (GCs) and open clusters (OCs) are
used. The tests by cluster member stars show a precision of about 10 per cent
with negligible zero-point offsets, for the derived distances of our sample
stars. The final sample covers a large volume of the Galactic disk(s) and halo
of $0<R<30$ kpc and $|Z|\leqslant15$ kpc. The rotation curve (RC) of the Milky
Way across radius of $5\lesssim R\lesssim25$ kpc have been accurately measured
with $\sim$ 54,000 stars of the thin disk population selected from the LRGB
sample. The derived RC shows a weak decline along $R$ with a gradient of
$-1.83\pm0.02$ $({\rm stat.}) \pm 0.07$ $({\rm sys.})$ km s$^{-1}$ kpc$^{-1}$,
in excellent agreement with the results measured by previous studies. The
circular velocity at the solar position, yielded by our RC, is $234.04\pm0.08$
$({\rm stat.}) \pm 1.36$ $({\rm sys.})$ km s$^{-1}$, again in great consistent
with other independent determinations. From the newly constructed RC, as well
as constraints from other data, we have constructed a mass model for our
Galaxy, yielding a mass of the dark matter halo of $M_{\rm{200}}$ =
($8.05\pm1.15$)$\times$10$^{11} \rm{M_\odot}$ with a corresponding radius of
$R_{\rm{200}}$ = $192.37\pm9.24$ kpc and a local dark matter density of
$0.39\pm0.03$ GeV cm$^{-3}$.
