Table 3 Time series forecasting results on \(\textrm{ETTm}_1\) datasets.
From: Fuzzy inference-based LSTM for long-term time series prediction
Models | Metric | 4 | 8 | 12 | 16 | 24 | 32 | 48 | 96 | 288 | Count |
|---|---|---|---|---|---|---|---|---|---|---|---|
ARIMA11 | MSE | 0.043 | 0.064 | 0.079 | 0.086 | 0.093 | 0.135 | 0.167 | 0.272 | 0.462 | 0 |
MAE | 0.182 | 0.203 | 0.214 | 0.219 | 0.221 | 0.264 | 0.303 | 0.399 | 0.558 | ||
GRU37 | MSE | 0.004 | 0.006 | 0.006 | 0.012 | 0.021 | 0.094 | 0.109 | 0.304 | 0.536 | 0 |
MAE | 0.032 | 0.047 | 0.051 | 0.076 | 0.117 | 0.244 | 0.263 | 0.433 | 0.597 | ||
DRNN38 | MSE | 0.004 | 0.005 | 0.006 | 0.011 | 0.020 | 0.092 | 0.107 | 0.301 | 0.557 | 0 |
MAE | 0.031 | 0.045 | 0.049 | 0.074 | 0.114 | 0.243 | 0.262 | 0.433 | 0.611 | ||
LSTM39 | MSE | 0.004 | 0.005 | 0.041 | 0.011 | 0.057 | 0.092 | 0.107 | 0.287 | 0.524 | 0 |
MAE | 0.031 | 0.123 | 0.151 | 0.074 | 0.178 | 0.243 | 0.262 | 0.420 | 0.584 | ||
FD-LSTM41 | MSE | 0.005 | 0.006 | 0.007 | 0.010 | 0.024 | 0.083 | 0.103 | 0.255 | 0.491 | 0 |
MAE | 0.034 | 0.043 | 0.054 | 0.072 | 0.116 | 0.232 | 0.264 | 0.431 | 0.561 | ||
FIS42 | MSE | 0.005 | 0.006 | 0.008 | 0.011 | 0.021 | 0.078 | 0.096 | 0.241 | 0.452 | 0 |
MAE | 0.032 | 0.045 | 0.052 | 0.070 | 0.109 | 0.233 | 0.271 | 0.433 | 0.521 | ||
Reformer22 | MSE | 0.020 | 0.037 | 0.056 | 0.081 | 0.095 | 0.114 | 0.163 | 0.920 | 1.108 | 0 |
MAE | 0.093 | 0.141 | 0.184 | 0.235 | 0.252 | 0.253 | 0.286 | 0.767 | 1.245 | ||
LogTrans23 | MSE | 0.003 | 0.005 | 0.006 | 0.010 | 0.019 | 0.078 | 0.085 | 0.199 | 0.411 | 1 |
MAE | 0.031 | 0.047 | 0.051 | 0.072 | 0.111 | 0.234 | 0.254 | 0.386 | 0.572 | ||
Efficient-att40 | MSE | 0.003 | 0.004 | 0.005 | 0.009 | 0.017 | 0.074 | 0.083 | 0.227 | 0.463 | 8 |
MAE | 0.029 | 0.041 | 0.044 | 0.068 | 0.107 | 0.251 | 0.251 | 0.413 | 0.593 | ||
FLSTM(Ours) | MSE | 0.003 | 0.004 | 0.005 | 0.008 | 0.018 | 0.071 | 0.090 | 0.194 | 0.382 | 12 |
MAE | 0.028 | 0.039 | 0.047 | 0.064 | 0.109 | 0.225 | 0.256 | 0.384 | 0.508 |