Dropout

Short-Term Power Load Forecasting Based on CNN-LSTM Network

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Short-Term Power Load Forecasting Based on CNN-LSTM Network

Click the blue text| Follow “Electrical Engineering” Abstract:Traditional neural networks have low accuracy in load forecasting with strong temporal correlation. To effectively improve the accuracy of short-term power load forecasting, a load forecasting method based on the combination of Convolutional Neural Network (CNN) and Long Short-Term Memory (LSTM) network is proposed. Five-dimensional load feature data … Read more

Overview of Dropout Applications in RNNs

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Overview of Dropout Applications in RNNs

【Introduction】This article provides the background and overview of Dropout, as well as a parameter analysis of its application in language modeling using LSTM / GRU recurrent neural networks. Author｜Adrian G Compiler｜Zhuanzhi (No secondary reproduction), Xiaoshi Organizer｜Yingying Dropout Inspired by the role of gender in evolution, Hinton et al. first proposed Dropout, which temporarily removes units … Read more

Overview of Dropout Application in RNNs

by
Overview of Dropout Application in RNNs

[Introduction] This article provides the background and overview of Dropout, as well as a parameter analysis of its application in language modeling using LSTM/GRU recurrent neural networks. Author｜Adrian G Compiled by｜Zhuanzhi Organized by｜Yingying Dropout Inspired by the role of gender in evolution, Hinton et al. first proposed Dropout, which temporarily removes units from the neural … Read more