MemDA: Forecasting Urban Time Series with Memory-based Drift Adaptation.
Zekun CaiRenhe JiangXinyu YangZhaonan WangDiansheng GuoHill Hiroki KobayashiXuan SongRyosuke ShibasakiPublished in: CoRR (2023)
Keyphrases
- weather forecasting
- forecasting accuracy
- financial time series
- logistics demand
- arma model
- exponential smoothing
- box jenkins
- chaotic time series
- short term
- hybrid model
- stock market
- support vector regression
- dynamic time warping
- forecasting model
- urban areas
- arima model
- demand forecasting
- non stationary
- turning points
- urban planning
- neural network
- mackey glass
- bp neural network
- neural network model
- phase space
- moving average
- subsequence matching
- grey model
- machine learning
- public transport
- financial data
- support vector machine
- garch model
- autoregressive
- transport network
- autoregressive integrated moving average
- short term prediction
- long term
- urban land
- concept drift
- forecast models
- data mining tasks
- exchange rate
- wind speed
- wind power
- error accumulation