准确的燃气负荷预测对于城市合理供应和调度能源起着非常重要的作用. 由于燃气负荷数据本身具有周期性, 随机性的复杂特点以及单阶段单预测模型的局限性, 本文提出了一种基于模糊编码遗传算法(Fuzzy Coding of Genetic Algorithms, FCGA)和改进的LSTM-BPNN残差修正模型的多阶段混合模型. 首先第一阶段先用LSTM进行燃气负荷...
dim=1).type(torch.FloatTensor)[:2000] /255. # shape from (2000,28,28) to (2000,1,28,28), valueinrange(0,1)test_y= test_loader.test_labels[:2000]# 定义模型classBPNN(nn.Module):
LSTM-BPNN沥青路面性能预测为解决传统网络模型预测沥青路面长期性能变化的局限性,同时考虑数据的基本特征和时序特征,提出了基于LSTM-BPNN(BP神经网络-长短期记忆网络)神经网络的沥青路面长期性能预测方法与流程,并基于美国长期路面性能数据库,进行了国际平整度指数IRI的预测及预测效果验证.结果表明:采用预测模型对沥青路面的...
Algorithms, FCGA)和改进的LSTM-BPNN 残差修正模型的多阶段混合模型. 首先第一阶段先用LSTM 进行燃气负荷初步预测, 然后计算出燃气负荷残差值, 第二阶段先用BPNN 去预测残差值, 然后用Adam 自适应学习率算法在学习过程中自动调节LSTM-BPNN 残差模型的学习率, 加快拟合速度, 接着用模糊编码遗传算法去优化BPNN 的...
首先,深度学习模型已经在各种研究领域中取得了很大的发展,主要说一下自己就CNN和RNN,LSTM模型的一些理解。(适合理解不透彻或者掌握不到精髓的读者,初学者可以看上面的博客,大神可以忽略) 首先,CNN是为了获取图像或者文本的local information 的,局部信息特征的获取比较擅长。但是光靠这些局部信息也不算完美啊,而且现在很...
This study adopts a new approach, SHapley Additive exPlanation (SHAP), to diagnose the table tennis matches based on a hybrid algorithm, namely Long Short-Term Memory–Back Propagation Neural Network (LSTM–BPNN). 100 male singles competitions (8535 rall
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Finally, the proposed novel hybrid Prophet-LSTM optimized by BPNN approach will be introduced. 2.1. ARIMA model selection An ARIMA model is a statistics analysis model for electrical load forecasting, and is mainly consists of three stages and three sections that are: Identification, Estimation and...
tensorflow1.1.0 + matplotlib2.0.2 + mysql-connector-python-rf2.2.2 + Structure common: common method such as data loading, model evaluation & model visualization etc. mlp: predict copper price using sklearn.neural_network.MLPRegressor lstm: predict copper price using keras.layers.recurrent.LSTM ...
Then, the restructured data are predicted\nby the Back Propagation Neural Network (BPNN) and Long Short-\nTerm Memory (LSTM) and weighted by Particle Swarm Optimization (PSO).\nFinally, the data are integrated to obtain the final results. The novel hybrid\nmodel makes allowances for the ...