|
ai-generated content (aigc) |
7 |
|
generative ai |
7 |
|
generative design |
7 |
|
generative method |
7 |
|
generative urban design |
7 |
|
human-machine collaboration |
7 |
|
urban form generation |
7 |
|
deep learning |
6 |
|
gis |
5 |
|
3d visualization |
4 |
|
building layout |
4 |
|
design scenario |
4 |
|
generative adversarial network (gan) |
4 |
|
national scale |
4 |
|
xgboost |
4 |
|
aigc |
3 |
|
air pollution |
3 |
|
air quality |
3 |
|
air taxi |
3 |
|
anthropogenic methane |
3 |
|
attention mechanism |
3 |
|
automated site planning |
3 |
|
built environment |
3 |
|
ch4 |
3 |
|
data-driven |
3 |
|
deep generative models |
3 |
|
demand analysis |
3 |
|
electric vertical take-off and landing (evtol) |
3 |
|
generative adversarial networks (gan) |
3 |
|
generative artificial intelligence (generative ai) |
3 |
|
global warming |
3 |
|
greenhouse gases |
3 |
|
human perception |
3 |
|
hybrid model |
3 |
|
land price estimation |
3 |
|
large language model |
3 |
|
leed |
3 |
|
literature review |
3 |
|
machine learning |
3 |
|
physics-based urban building energy modeling |
3 |
|
planning guidance |
3 |
|
recursive feature elimination |
3 |
|
remote sensing |
3 |
|
road safety |
3 |
|
sectoral emissions |
3 |
|
street view images |
3 |
|
urban air mobility (uam) |
3 |
|
urban air mobility life cycle |
3 |
|
air pollution control |
2 |
|
air quality index |
2 |
|
air quality prediction |
2 |
|
association rule analysis |
2 |
|
association rule mining |
2 |
|
bayesian optimization |
2 |
|
bi-directional estimation |
2 |
|
big data |
2 |
|
big data techniques |
2 |
|
biochemical oxygen demand |
2 |
|
bootstrap-resampling-data-balancing method |
2 |
|
building energy |
2 |
|
climate factors |
2 |
|
cost management |
2 |
|
covid-19 |
2 |
|
deep matrix factorization |
2 |
|
deep neural network |
2 |
|
dynamic programming |
2 |
|
electric power |
2 |
|
energy use intensity |
2 |
|
enhanced learning model |
2 |
|
ensemble method |
2 |
|
explainable ai |
2 |
|
feature analysis |
2 |
|
feature importance |
2 |
|
felony assault |
2 |
|
geographic information system |
2 |
|
geographic lstm |
2 |
|
gradient boost decision tree |
2 |
|
grid importance rank |
2 |
|
harbor water |
2 |
|
hourly prediction |
2 |
|
humidity |
2 |
|
ignition process |
2 |
|
imbalanced dataset |
2 |
|
lag-flstm |
2 |
|
land values per square foot |
2 |
|
lightgbm |
2 |
|
long short-term memory (lstm) |
2 |
|
long-interval consecutive missing values |
2 |
|
low-cost sensor |
2 |
|
macro factors |
2 |
|
meteorology |
2 |
|
missing data |
2 |
|
modular construction |
2 |
|
multivariate inputs |
2 |
|
neural network |
2 |
|
pedestrian volume |
2 |
|
place of interest |
2 |
|
pm 2.5 |
2 |
|
pm2.5 |
2 |
|
pollutant emission |
2 |
|
powerline vegetation faults |
2 |
|
road-based analysis |
2 |
|
run-off-road accidents |
2 |
|
satellite |
2 |
|
semi-supervised learning |
2 |
|
siberia |
2 |
|
sparse matrix |
2 |
|
spatial analysis |
2 |
|
spatial extrapolation |
2 |
|
spatial proximity analysis |
2 |
|
spatiotemporal distribution |
2 |
|
the most influential areas |
2 |
|
traffic accident fatality |
2 |
|
traffic fatality rates |
2 |
|
transfer learning |
2 |
|
unlabeled samples |
2 |
|
urban building energy modeling |
2 |
|
urban buildings |
2 |
|
urban morphology |
2 |
|
variable importance |
2 |
|
wildfire |
2 |
|
work package |
2 |
|
3d printing |
1 |
|
adaboost decision tree |
1 |
|
air quality forecasting |
1 |
|
artificial neural network |
1 |
|
artificial neural network (ann) |
1 |
|
automated machine learning |
1 |
|
bi-directional long short-term memory |
1 |
|
building information modeling |
1 |
|
building structure |
1 |
|
case-based reasoning |
1 |
|
city planning |
1 |
|
classification |
1 |
|
clean air action plan |
1 |
|
climate change |
1 |
|
clustering |
1 |
|
computational design |
1 |
|
construction automation |
1 |
|
credit achievement |
1 |
|
data mining |
1 |
|
decision support system |
1 |
|
decision support tool |
1 |
|
emission |
1 |
|
energy conservation |
1 |
|
energy use intensity (eui) |
1 |
|
environmental policy |
1 |
|
factors analysis |
1 |
|
feature selection |
1 |
|
geographic information system (gis) |
1 |
|
greedy forward search |
1 |
|
green building |
1 |
|
green building market |
1 |
|
grid-based analysis |
1 |
|
human exposure |
1 |
|
industrialized building |
1 |
|
influential feature analysis |
1 |
|
intersection cycling safety |
1 |
|
inverse distance weighting |
1 |
|
large temporal resolution |
1 |
|
leed-nc v2009 |
1 |
|
long short-term memory |
1 |
|
multi-family residential buildings |
1 |
|
neural networks |
1 |
|
new stations |
1 |
|
nitrogen dioxide |
1 |
|
non-linear |
1 |
|
non-linear machine learning |
1 |
|
numerical simulation |
1 |
|
origin-destination oriented crash rate |
1 |
|
ozone |
1 |
|
percentage of average score (pas) |
1 |
|
performance optimisation |
1 |
|
prefabrication |
1 |
|
public health |
1 |
|
random forest |
1 |
|
random forests (rf) |
1 |
|
random forests algorithm |
1 |
|
regional effect |
1 |
|
related credits |
1 |
|
satellite observation |
1 |
|
satellite observations |
1 |
|
shap-based geospatial analysis |
1 |
|
spatial transfer learning |
1 |
|
spatialtemporal correlation |
1 |
|
spatiotemporal phenomena |
1 |
|
support vector regression (svr) |
1 |
|
svm |
1 |
|
target credit selection |
1 |
|
traffic fatality |
1 |
|
urbanization |
1 |
|
visual risk factors |
1 |
