1.1 Sequence prediction 1.2 所处理的实际场景 对于调配各地区电力的大型变压器,单次调整后会持续运行数周,保证电网的稳定。但这就需要对未来较长范围内的变压器负载有相对较为精确的估计。 1.3 当前预测方法 未来近期预测 Near future prediction鲁棒性不足,不能保证变压器在接下来两周内保持稳定运行。 粗粒度预测 C...
Society Event Prediction社会事件预测 Coarse粗 Long sequence长时间序列 Inefficient效率低下的 Ground Truth地面实况 时间序列经典算法这里可以认真听一下 涉及论文里的优缺点评价 sequence序列 log scale对数尺度 Encoder hidden states编码器隐藏状态 Decoder hidden states解码器隐藏状态 Score each hidden state给每个隐藏...
parser.add_argument('--pred_len', type=int, default=24, help='prediction sequence length') # Informer decoder input: concat[start token series(label_len), zero padding series(pred_len)] parser.add_argument('--enc_in', type=int, default=7, help='encoder input size') parser.add_argumen...
policy-planning and investment-protecting. (b) The prediction capacity of existing methods limits LSTF’s performance. E.g., starting from length=48, MSE rises unacceptably high, and the inference speed drops rapidly. 在Informer中提出,在长序列预测过程中,如果序列越长,那么速度会越慢,同时,效果也...
The performance of the proposed temperature prediction model is evaluated via objective measures, including the root-mean-square error (RMSE) and mean absolute error (MAE) over different timeframes, ranging from 6 to 336 h. The experiments showed that the proposed model relatively reduced the ...
y=a+b*x+e (error term), [error term is the value needed to correct for a prediction error between the observed and predicted value] => y=a+y= a+ b1x1+ b2x2+...+e, for multiple independent variables. 1. 2. 在一个线性方程中,预测误差可以分解为2个子分量。一个是偏差,一个是方差...
Prediction of Stock Closing Prices Based on Attention Mechanism[C]//2020 16th Dahe Fortune China Forum and Chinese High-educational Management Annual Academic Conference (DFHMC). IEEE, 2020: 244-248. 章宁, 闫劭彬, 范丹. 基于深度学习的收益率预测与投资组合模型[J]. 统计与决策, 2022年, 第23期...
you can also use more detailed freq like 15min or 3hargs.checkpoints = './checkpoints' # location of model checkpointsargs.seq_len = 20 # input sequence length of Informer encoderargs.label_len = 10 # start token length of Informer decoderargs.pred_len = 5 # prediction sequence length...
This paper proposes an Informer-based temperature prediction model to leverage data from an automatic weather station (AWS) and a local data assimilation and prediction system (LDAPS), where the Informer as a variant of a Transformer was developed to better deal with time series data. Recently,...
AGCNT: Adaptive Graph Convolutional Network for Transformer-based Long Sequence Time-Series Forecasting [2205.04885] Adaptive Graph Convolutional Network Framework for Multidimensional Time Series Prediction (http://arxiv.org) Informer: Beyond Efficient Transformer for Long Sequence Time-Series Forecasting ...