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Partitioning multi-layer edge network for neural network collaborative computing
There is a trend to deploy neural network on edge devices in recent years. While the mainstream of research often concerns with single edge device...
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The cross-sectional stock return predictions via quantum neural network and tensor network
In this paper, we investigate the application of quantum and quantum-inspired machine learning algorithms to stock return predictions. Specifically,...
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An integrated simplicial neural network with neuro-fuzzy network for graph embedding
In recent years, graph neural network (GNN) has become the main stream for most of recent researches due to its powers in dealing with complex graph...
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modSwish: a new activation function for neural network
The activation functions are extremely important to neural networks since they are responsible for learning the abstract characteristics of the data...
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Neural Network Approaches for Recommender Systems
AbstractRecommender systems are special algorithms that allow users to receive personalized recommendations on topics that interest them. Systems of...
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Compact eternal diffractive neural network chip for extreme environments
Artificial intelligence applications in extreme environments place high demands on hardware robustness, power consumption, and speed. Recently,...
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Construction of Measurement Model for Ultimate Carrying Capacity of Medium Voltage Distribution Network Based on Genetic Neural Network
In order to avoid the overload fault of distribution network and ensure the safety and stability of power supply of distribution network, a measuring...
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Fuzzy Neural Network
Fuzzy neural network combines fuzzy computing and artificial neural network. Fuzzy neural network inherits the characteristics of both fuzzy logic...
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Bootstrapped Dendritic Neuron Model Artificial Neural Network for Forecasting
The dendritic neuron model artificial neural network, in which the dendrites in the biological neuron are added to the artificial neural network...
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Artificial Neural Network
Artificial neural network is the core of deep learning algorithms and the forefront of artificial intelligence. Its inspiration comes from neurons...
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A binary-domain recurrent-like architecture-based dynamic graph neural network
The integration of Dynamic Graph Neural Networks (DGNNs) with Smart Manufacturing is crucial as it enables real-time, adaptive analysis of complex...
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RSGNN: residual structure graph neural network
Compared to conventional artificial neural networks, Graph Neural Networks (GNNs) better handle graph-structured data. Graph topology plays an...
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Node importance Evaluation Model of Opportunistic Network Based on Improved Graph Neural Network
In order to improve the node importance evaluation effect of the opportunistic network, this paper applies the improved graph neural network to the...
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Memristive discrete chaotic neural network and its application in associative memory
Chaotic behaviors existing in biological neurons play an important role in the brain’s associative memory. Hence, chaotic neural networks have been...
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Convolutional Neural Network
Convolutional neural network is one of the most important networks in deep learning. Different from common artificial neural network, the main...
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Adaptive Neural Network Control of Space-Mission Universal Mechatronic Module
AbstractA review of methods for adaptive neural network control of actuators based on a stepper motor is presented. A model of a universal...
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Design of Computer Network Security Defense System Based on Artificial Intelligence and Neural Network
In order to improve the effect of computer security defense, this paper applies artificial intelligence technology and neural network technology to...
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Neural-Network Prediction of Tool Wear
AbstractThe potential of neural networks in predicting the wear resistance of cutting tools when machining workpieces with standard elements is...
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Secure and privacy in healthcare data using quaternion based neural network and encoder-elliptic curve deep neural network with blockchain on the cloud environment
The security and privacy of healthcare data are crucial aspects within the healthcare industry, as accurate diagnoses rely on medical professionals...
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A design of power prediction algorithm based on health assessment optimized neural network
Wind power prediction holds significant value for the stability of the electrical grid when wind power is connected to the grid. Using neural...
