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Explainable Enterprise Credit Rating via Deep Feature Crossing Network [article]

Weiyu Guo, Zhijiang Yang, Shu Wu, Fu Chen
2021 arXiv   pre-print
Therefore, in this paper, we propose a novel network to explicitly model the enterprise credit rating problem using DNNs and attention mechanisms.  ...  The proposed model realizes explainable enterprise credit ratings.  ...  In this paper, to model the credit ratings of enterprises using deep neural network with output readable explanations, we propose a novel attention mechanism based deep neural network called DeepCross  ... 
arXiv:2105.13843v1 fatcat:h7jfzrkxvrgx5eyekmgf3qrkam

Advertising Click-Through Rate Prediction Based on CNN-LSTM Neural Network

Danqing Zhu, Syed Hassan Ahmed
2021 Computational Intelligence and Neuroscience  
CNN convolution neural network is used to train the prediction model.  ...  To solve the above problems, this paper proposes a CNN-LSTM (convolutional neural network-long short-term memory) convolution hybrid neural network algorithm to predict the click-through rate of advertisements  ...  Based on the use of attention mechanism model in deep learning neural network algorithm, we combine dynamic network with users' click interest in advertising.  ... 
doi:10.1155/2021/3484104 fatcat:de33jd5gjjbzhdrwdr5xby5avm

Research on Performance Prediction of Technological Innovation Enterprises Based on Deep Learning

Huan Liu, Yuanpeng Zhang
2021 Wireless Communications and Mobile Computing  
neural network model for performance prediction of scientific and technological innovation enterprises.  ...  Using the deep belief network model in deep learning combined with support vector regression to establish a prediction model for technological innovation enterprises, this paper proposes a convolutional  ...  I also found that whether it is in deep neural networks or convolutional neural networks, the direct use of enterprise difference features will not improve the effect of the experiment, but will have side  ... 
doi:10.1155/2021/1682163 fatcat:bxkk5i46svfkjaqctvvfg3mksa

Enterprise Strategic Management From the Perspective of Business Ecosystem Construction Based on Multimodal Emotion Recognition

Wei Bi, Yongzhen Xie, Zheng Dong, Hongshen Li
2022 Frontiers in Psychology  
This paper aims to study a multimodal ER method based on attention mechanism.  ...  Then, two datasets, CMU-MOSI and CMU-MOSEI, are selected to design the scheme for multimodal ER based on self-attention mechanism.  ...  results. (2) A multimodal ER based on self-attention mechanism and neural network is proposed.  ... 
doi:10.3389/fpsyg.2022.857891 pmid:35310264 pmcid:PMC8927019 doaj:82cf2c71b7bf4e4f9bdeda763b6e1939 fatcat:hssh4dpwzbahvpv5vyupuuoxuu

Research on the Correlation Model and Algorithm between Intangible Assets and Enterprise Value of Sports Listed Enterprises Based on Deep Learning

Xiaoyan Dong, Ziqi Xu, Hasan Ali Khattak
2022 Mobile Information Systems  
through parallel neural fuzzy network calculation, so as to verify the correlation between intangible value and enterprise value.  ...  analysis model algorithm based on deep learning and the method of constructing multiple regression model.  ...  Carry out multiple regression analysis on the relevant variables, introduce machine learning, use neural network algorithm to analyze the impact of variables on enterprise value, and explain the above  ... 
doi:10.1155/2022/3540011 fatcat:weynw7fnz5duxk6egcgvoew4vi

Risk Management of Investment Projects Based on Artificial Neural Network

Limei Deng, Ying Chang, Jun Ye
2022 Wireless Communications and Mobile Computing  
It establishes a benefit evaluation model based on an artificial neural network, from the analysis and consideration of 4 groups of experiments, comparing four sets of data: BP network convergence rate  ...  , artificial neural network identification efficiency, enterprise risk, artificial neural network output, and error; it is concluded that the relative risk is reduced by about 20% after using the artificial  ...  Based on the dynamics of inertial impulses, the scientific community has discovered that it can be used to influence the rate of learning.  ... 
doi:10.1155/2022/5606316 fatcat:i6xcsuwhfnbz3fq6r3dremet3e

A Recommendation Model for College Career Entrepreneurship Projects Based on Deep Learning

Yuan Feng, Weixian Huang, Deepak Gupta
2021 Wireless Communications and Mobile Computing  
A deep neural network was established for the extraction of the hidden features of entrepreneurial projects, and a convolution neural network was used to process the text description information of entrepreneurial  ...  Based on the ConvMF algorithm, this paper proposes an entrepreneurial project recommendation algorithm based on a deep neural network and matrix decomposition.  ...  recommendation algorithm based on a deep neural network and matrix decomposition.  ... 
doi:10.1155/2021/1418333 fatcat:445jn3adzzgv7gs52pqxdbx2ja

Volatility Forecasting for High-Frequency Financial Data Based on Web Search Index and Deep Learning Model

Bolin Lei, Boyu Zhang, Yuping Song
2021 Mathematics  
change rate, etc., as input indicators, and finally employ the deep learning model via temporal convolutional networks (TCN) to forecast the volatility under high-frequency financial data.  ...  We found that the prediction accuracy of the TCN model with investor attention is better than those of the TCN model without investor attention, the traditional econometric model as the generalized autoregressive  ...  Methods and Empirical Procedure TCN Model In deep learning algorithms, the modeling time series is mainly based on a recurrent neural network (RNN), while convolutional neural networks (CNN), as in LeCun  ... 
doi:10.3390/math9040320 fatcat:p7pqquqv2vazrbpzpsshdk44o4

Multi-context Attention Fusion Neural Network for Software Vulnerability Identification [article]

Anshul Tanwar, Hariharan Manikandan, Krishna Sundaresan, Prasanna Ganesan, Sathish Kumar Chandrasekaran, Sriram Ravi
2021 arXiv   pre-print
The AI architecture is an Attention Fusion model, that combines the effectiveness of recurrent, convolutional and self-attention networks towards decoding the vulnerability hotspots in code.  ...  Thus helping a developer to quickly focus on the vulnerable code sections; and this becomes the "explainable" part of the vulnerability detection.  ...  For vulnerability classification, conventional approaches would pick any one of the neural architectures like Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN) or attention to solve  ... 
arXiv:2104.09225v1 fatcat:qwpzhbjp35a7xdach6rrnihmxq

Credit Evaluation of SMEs Based on GBDT-CNN-LR Hybrid Integrated Model

Lei Zhang, Qiankun Song, Yingjie Wang
2022 Wireless Communications and Mobile Computing  
Based on previous studies, this paper proposes a two-layer feature extraction method based on Gradient Boosting Decision Tree (GBDT) and Convolutional Neural Network (CNN).  ...  First, based on the original features, GBDT is used to combine and automatically screen them, the missing values in the feature are processed, and the transformed high-dimensional sparse features are obtained  ...  Convolutional Neural Network (CNN) consists of one or more convolutional layers and a fully connected layer, which also includes associated weights layers and pooling layers.  ... 
doi:10.1155/2022/5251228 fatcat:vxt3kydhjzfm5cerwbbxrbueay

Design of hybrid neural networks of the ensemble structure

Victor Sineglazov, Anatoly Kot
2021 Eastern-European Journal of Enterprise Technologies  
This paper considers the structural-parametric synthesis (SPS) of neural networks (NNs) of deep learning, in particular convolutional neural networks (CNNs), which are used in image processing.  ...  That is ensured by using unique blocks that determine their essential features, namely, the compression and excitation unit, the attention module convolution unit, the channel attention module, the spatial  ...  based on width; -CNN based on the use of the features map; -CNN based on boosting channels; -CNN based on the use of the attention mechanism.  ... 
doi:10.15587/1729-4061.2021.225301 fatcat:ze4ufr667ratjpuggp4bb4zv5m

AAFM: Adaptive Attention Fusion Mechanism for Crowd Counting

Zuodong Duan, Huimin Chen, Jiahao Deng
2020 IEEE Access  
ADAPTIVE ATTENTION FUSION MECHANISM The adaptive attention fusion mechanism is used in the proposed attentional neural network (AAFM).  ...  RELATED WORK Our attentional fusion neural network (AAFM) implants the convolution network and the attention mechanism into an encoder-decoder framework, establishing a novel and compact deep model for  ...  In the past five years, he has presided over more than 10 National Natural Fund, Field Fund, Key Laboratory Fund, and Enterprise Horizontal Projects. He has published more than 40 related papers.  ... 
doi:10.1109/access.2020.3012818 fatcat:rx2qkgs6svb4beqrkjs7rhpz2u

COVIDNet-CT: A Tailored Deep Convolutional Neural Network Design for Detection of COVID-19 Cases From Chest CT Images

Hayden Gunraj, Linda Wang, Alexander Wong
2020 Frontiers in Medicine  
Motivated by this, in this study we introduce COVIDNet-CT, a deep convolutional neural network architecture that is tailored for detection of COVID-19 cases from chest CT images via a machine-driven design  ...  so ensure that COVIDNet-CT makes predictions based on relevant indicators in CT images.  ...  ., and Hewlett Packard Enterprise Co.  ... 
doi:10.3389/fmed.2020.608525 pmid:33425953 pmcid:PMC7786372 fatcat:hphos2bomfgq5oohl3zfqbghbu

The Acceptance Status of Traditional Moral Culture in Colleges and Universities Using Convolutional Neural Network

Bingduan Liu
2022 Scientific Programming  
A model based on convolutional neural networks is suggested for predicting college students' embrace of traditional moral values.  ...  Actively borrowing their essence can help promote the development of Chinese culture, but we must also pay attention to active defense and resistance against the dregs of culture.  ...  based on convolutional neural networks.  ... 
doi:10.1155/2022/7868591 doaj:fb424a465a9d4834bfb38f309d731591 fatcat:m7whm3hhk5d6xgqrrzojmepiom

Construction of Value Chain E-Commerce Model Based on Stationary Wavelet Domain Deep Residual Convolutional Neural Network

Chenyuan Wang, Wei Wang
2020 Complexity  
e-commerce department as the core department of the enterprise is proposed.  ...  By training the optimal parameters of the deep residual network and comparing the results with other models, the method of this paper has a good effect against the sample.  ...  Researches on image enhancement and noise processing based on convolutional neural networks have proposed related methods [30, 31] .  ... 
doi:10.1155/2020/6611325 fatcat:uo6dbf3rhne35f3apna5exvv7a
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