… input (NARX) recurrent neural network (RNN) and time delay neural network (TDNN) to …
heuristics, metaheuristics provide a general process that can effectively reduce complexity …

… (1) Metaheuristics and their applications in intelligent automation and global optimization
including evolutionary algorithms, … (CNN), and recurrent neural networks (RNNs); (4) Aspects of …

… (convolutional neural network,CNN)和基于循环神 经网络(recurrent neural networks,RNN)的…
Short-term electricity load forecasting based on feature selection and least squares support …

… we have to apply some heuristic methods for optimization based on connectivity of the network.
The calculation structure of connectivity of complex network is analyzed in the paper. The …

… Prediction of maximum ground settlement induced by shield tunneling based on
recurrent neural network[J]. China Civil Engineering Journal, 2020, 53(Suppl.1): 13-19. …

… in recent years, and meta-heuristic algorithms are considered effective methods for solving
… in meta-heuristic algorithms for solving LBOPs, including meta-heuristic algorithms with and …

… 1.1 门控循环单元神经网络 门控循环单元(GRU)是基于循环神经网络(Recurrent neural …
Optimization of support vector machine through the use of metaheuristic algorithms in forecasting …

… Behavior and stateof-health monitoring of Li-ion batteries using impedance spectroscopy
and recurrent neural networks[J]. International Journal of Electrical Power &Energy …

… Guan YY, Cai SM, Shang MS (2014) Recommendation algorithm based on item quality and
user rating preferences. Front Comput Sci 8 (2): 289–297 271. Guo DK, Liu YH, Jin H et al (…

… prediction: An approach based on bidirectional quasi recurrent neural network with attention.
Acta … Feature selection and optimal decision tree construction of complex power quality …