AIMC Topic: Neural Networks, Computer

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Research on Wind Power Short-Term Forecasting Method Based on Temporal Convolutional Neural Network and Variational Modal Decomposition.

Sensors (Basel, Switzerland)
Wind energy reserves are large worldwide, but their randomness and volatility hinder wind power development. To promote the utilization of wind energy and improve the accuracy of wind power prediction, we comprehensively consider the influence of win...

Deep Learning-Based Remaining Useful Life Estimation of Bearings with Time-Frequency Information.

Sensors (Basel, Switzerland)
In modern industrial production, the prediction ability of remaining useful life of bearings directly affects the safety and stability of the system. Traditional methods require rigorous physical modeling and perform poorly for complex systems. In th...

Artificial intelligence-informed planning for the rapid response of hazard-impacted road networks.

Scientific reports
Post-hazard rapid response has emerged as a promising pathway towards resilient critical infrastructure systems (CISs). Nevertheless, it is challenging to scheme the optimal plan for those rapid responses, given the enormous search space and the hard...

Electrospray mode discrimination with current signal using deep convolutional neural network and class activation map.

Scientific reports
The electrospray process has been extensively applied in various fields, including energy, display, sensor, and biomedical engineering owing to its ability to generate of functional micro/nanoparticles. Although the mode of the electrospray process h...

Adversarial attacks and adversarial robustness in computational pathology.

Nature communications
Artificial Intelligence (AI) can support diagnostic workflows in oncology by aiding diagnosis and providing biomarkers directly from routine pathology slides. However, AI applications are vulnerable to adversarial attacks. Hence, it is essential to q...

Predicting respiratory motion using a novel patient specific dual deep recurrent neural networks.

Biomedical physics & engineering express
Real-time tracking of a target volume is a promising solution for reducing the planning margins and both dosimetric and geometric uncertainties in the treatment of thoracic and upper-abdomen cancers. Respiratory motion prediction is an integral part ...

Generative and interpretable machine learning for aptamer design and analysis of in vitro sequence selection.

PLoS computational biology
Selection protocols such as SELEX, where molecules are selected over multiple rounds for their ability to bind to a target of interest, are popular methods for obtaining binders for diagnostic and therapeutic purposes. We show that Restricted Boltzma...

Bifurcations of a Fractional-Order Four-Neuron Recurrent Neural Network with Multiple Delays.

Computational intelligence and neuroscience
This paper investigates the bifurcation issue of fractional-order four-neuron recurrent neural network with multiple delays. First, the stability and Hopf bifurcation of the system are studied by analyzing the associated characteristic equations. It ...

Application of Price Competition Model Based on Computational Neural Network in Risk Prediction of Transnational Investment.

Computational intelligence and neuroscience
Aiming at the scenario where edge devices rely on cloud servers for collaborative computing, this paper proposes an efficient edge-cloud collaborative reasoning method. In order to meet the application's specific requirements for delay or accuracy, a...

Research on Risk Assessment and Prediction of RMB Internationalization Based on the PCA-SA-BPNN Model.

Computational intelligence and neuroscience
This paper combines principal component analysis, a BP neural network, and a simulated annealing algorithm, to construct a PCA-SA-BPNN risk forecast model to evaluate and predict the RMB internationalization risk status of China. First, we analyze th...