Our running code and detailed parameter settings can be found in Experiment Setting.
Attributes | New York City | Chicago | DC |
---|---|---|---|
Time span | 2013.03-2017.09 | 2013.07-2017.09 | 2013.07-2017.09 |
Number of riding records | 49,100,694 | 13,130,969 | 13,763,675 |
Number of stations | 820 | 585 | 532 |
Following shows a map-visualization of bike stations in NYC.
NYC | Chicago | DC | |
---|---|---|---|
HM | 3.99224 | 2.97693 | 2.63165 |
ARIMA(C) | 5.60928 | 3.83584 | 3.60450 |
XGBoost | 4.12407 | 2.92569 | 2.65671 |
GBRT | 3.99907 | 2.84257 | 2.61768 |
ST_MGCN (G/DCI) | 3.72380 | 2.88300 | 2.48560 |
DCRNN(G/D C) | 4.18666 | 3.27759 | 3.08616 |
LSTM (C) | 4.55677 | 3.37004 | 2.91518 |
STMeta-V1 | 3.50475 | 2.65511 | 2.42582 |
STMeta-V2 | 3.43870 | 2.66379 | 2.41111 |
STMeta-V3 | 3.47834 | 2.66180 | 2.38844 |
Attributes | Xi'an | Chengdu |
---|---|---|
Time span | 2016.10-2016.11 | 2016.10-2016.11 |
Number of riding records | 5,922,961 | 8,439,537 |
Number of stations | 256 | 256 |
Following shows a map-visualization of 256 grid-based ride-sharing stations in Chengdu.
Xi’an | Chengdu | |
---|---|---|
HM | 6.18623 | 7.35477 |
ARIMA(C) | 9.47478 | 12.52656 |
XGBoost | 6.73346 | 7.73836 |
GBRT | 6.44639 | 7.58831 |
ST-ResNet | 6.08476 | 7.14638 |
ST_MGCN (G/DCI) | 5.87456 | 7.03217 |
DCRNN(G/D C) | 8.20254 | 11.50550 |
LSTM (C) | 7.39970 | 10.11386 |
STMeta-V1 (G/DCI) | 5.89154 | 7.06246 |
STMeta-V2(G/DCI) | 5.75596 | 7.09710 |
STMeta-V3(G/DCI) | 5.95507 | 7.04358 |
Attributes | Chongqing | Shanghai |
---|---|---|
Time span | 2016.08-2017.07 | 2016.07-2016.09 |
Number of riding records | 409,277,117 | 333,149,034 |
Number of stations | 113 | 288 |
Following shows a map-visualization of 288 metro stations in Shanghai.
Chongqing | Shanghai | |
---|---|---|
HM | 120.30723 | 197.97092 |
ARIMA(C) | 578.18563 | 792.1597 |
XGBoost | 117.05069 | 185.00447 |
GBRT | 113.92276 | 186.74502 |
ST_MGCN (G/DCI) | 118.86668 | 181.55171 |
DCRNN(G/D C) | 122.31121 | 326.97357 |
LSTM (C) | 196.175732 | 368.8468 |
STMeta-V1 (G/DCI) | 92.74990 | 151.11746 |
STMeta-V2(G/DCI) | 98.86152 | 158.21953 |
STMeta-V3(G/DCI) | 101.7806 | 156.58867 |
The period and trend features are more obvious in Metro dataset, so the performance is poor if only use closeness feature.
Attributes | Beijing |
---|---|
Time span | 2018.03-2018.08 |
Number of riding records | 1,272,961 |
Number of stations | 629 |
Following shows a map-visualization of 629 EV charging stations in Beijing.
Beijing | |
---|---|
HM | 1.01610 |
ARIMA(C) | 0.98236 |
XGBoost | 0.83381 |
GBRT | 0.82814 |
ST_MGCN (G/DC) | 0.82714 |
DCRNN(G/D C) | 0.98871 |
LSTM (C) | 1.58560 |
STMeta-V1 (G/DC) | 0.815518 |
STMeta-V2(G/DC) | 0.82144 |
STMeta-V3(G/DC) | 0.81541 |