Enterprise Profit Forecast Model Based on Long Short-Term Memory Neural Network

2021 ◽  
Author(s):  
Zhang Qianyu ◽  
Liu Dongping ◽  
Zhu Xueying ◽  
Chen Huaisen ◽  
Zhou Xiaozhou
Keyword(s):  
Neural Network ◽  
Short Term Memory ◽  
Forecast Model ◽  
Short Term ◽  
Term Memory ◽  
Model Based ◽  
Long Short Term Memory

scholarly journals A Correction Method of Environmental Meteorological Model Based on Long‐Short‐Term Memory Neural Network

2019 ◽  
Vol 6 (11) ◽  
pp. 2214-2226 ◽  
Author(s):  
Yuliang Dai ◽  
Zhenyu Lu ◽  
Hengde Zhang ◽  
Tianming Zhan ◽  
Jia Lu ◽  
...  
Keyword(s):  
Neural Network ◽  
Short Term Memory ◽  
Correction Method ◽  
Short Term ◽  
Meteorological Model ◽  
Term Memory ◽  
Model Based ◽  
Long Short Term Memory

scholarly journals Bridge Temperature Prediction Model Based on Long-Short Term Memory Neural Network

2021 ◽  
Vol 1966 (1) ◽  
pp. 012013
Author(s):  
Jingxiao Shu ◽  
Dongyue Zhao ◽  
Xuda Zheng ◽  
Yiwen Li ◽  
Yufeng Zhang
Keyword(s):  
Neural Network ◽  
Prediction Model ◽  
Short Term Memory ◽  
Short Term ◽  
Temperature Prediction ◽  
Term Memory ◽  
Model Based ◽  
Long Short Term Memory

scholarly journals Construction of the Open Oral Evaluation Model Based on the Neural Network

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Zhixin Chen ◽  
Xu Zhang ◽  
Zhiyuan Li ◽  
Anchu Li
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Oral Language ◽  
Short Term Memory ◽  
Evaluation Model ◽  
Short Term ◽  
Term Memory ◽  
Scoring Model ◽  
Model Based ◽  
Long Short Term Memory

According to the problem of low efficiency and low scoring accuracy of the traditional oral language scoring system, this study builds an open oral language evaluation model based on the basic principles of deep learning technology. Firstly, the basic methods of the convolutional neural network (CNN) and long short-term memory (LSTM) neural network are introduced. Then, we combine the convolutional neural network (CNN) and long short-term memory (LSTM) neural network to design an open oral scoring model based on CNN + LSTM, which divides the oral evaluation model into the speech scoring model and text scoring model and makes a specific implementation of two scoring models, respectively. An experimental environment is then built to preprocess the data, and finally, the model built in this study is trained and simulated. The experimental results show that the CNN + LSTM network evaluation model has a better comprehensive scoring performance, higher scoring efficiency, and higher accuracy and has feasibility and practicability.

scholarly journals An Improved Long Short-Term Memory Neural Network for Macroeconomic Forecast

2020 ◽  
Vol 34 (5) ◽  
pp. 577-584
Author(s):  
Lipeng Wang
Keyword(s):  
Neural Network ◽  
Short Term Memory ◽  
Low Frequency ◽  
Forecast Model ◽  
Evaluation Index System ◽  
Short Term ◽  
Term Memory ◽  
Macroeconomic Forecast ◽  
Long Short Term Memory ◽  
Missing Items

The statistics and cyclical swings of macroeconomics are necessary for exploring the internal laws and features of the market economy. To realize intelligent and efficient macroeconomic forecast, this paper puts forward a macroeconomic forecast model based on improved long short-term memory (LSTM) neural network. Firstly, a scientific evaluation index system (EIS) was constructed for macroeconomy. The correlation between indices was measured by Spearman correlation coefficient, and the index data were preprocessed by interpolating the missing items and converting low-frequency series into high-frequency series. Next, the corresponding mixed frequency dataset was constructed, followed by the derivation of the state space equation. Then, the LSTM neutral network was optimized by the Kalman filter or macroeconomic forecast. The effectiveness of the proposed forecast method was verified through experiments. The research results lay a theoretical basis for the application of LSTM in financial forecasts.

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