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We shall discuss various Barron type spaces arising from neural networks. The relations among these spaces will be clarified, and we shall also establish the relationship between Barron type spaces an...
The focus of this talk is on the numerical methods used to identify parameters in partial differential equations. Typically, an optimization approach is used to solve this class of inverse problems, w...
With the advantages of fast calculating speed and high precision, the physics-informed neural network method opens up a new approach for numerically solving nonlinear partial differential equations. B...
Artificial intelligence and machine learning have become crucial tools for medical imaging, autonomous vehicles and many other applications, but engineers warn that the exponential increase in compute...
The number of distributed Photovoltaic (PV) plants that produce electricity has been significantly increased, and issue of monitoring and maintaining a PV plant has become of great importance and invo...
For all the improvements in computer technology over the years, we still struggle to recreate the low-energy, elegant processing of the human brain. Now, researchers at Stanford University and Sandia ...
Gruhn, Matthias, John Guckenheimer, Bruce Land, and Ronald M. Harris-Warrick. Dopamine modulation of two delayed rectifier potassium currents in a small neural network. J Neurophysiol 94: 2888–2900,...
The Line flow Contingency Selection and Ranking (CS & R) is performed to rank the critical contingencies in order of their severity. An Artificial Neural Network based method for MW security assessmen...
For water color remote sensing study of inland water body, terrestrial satellite is often a good data source, because it has high spatial resolution. However, the precision of water color remote sens...
The artificial neural networks (ANNs), among different soft computing methodologies are widely used to meet the challenges thrown by the main objectives of data mining classification techniques, due t...
Approaches to machine intelligence based on brain models use neural networks for generalization but they do so as signal processing black boxes. In reality, the brain consists of many modules that ope...
Monitoring and predicting machine components' faults play an important role in maintenance actions. Developing an intelligent system is a good way to overcome the problems of maintenance management. ...
以前馈型BP神经网络进行双目立体视觉系统的摄像机标定研究,基于Harris角点提取,提出了增加约束的改进方法,从而提高网络训练样本集的数据精度;探讨了神经网络的欠泛化、过泛化问题,综合运用归一化、提前终止等多种策略,进一步提高网络泛化能力,并与经典标定方法进行对比。试验结果表明,该方法能够获得较高的摄像机标定精度。
The leveling adjustment process of cable-driven parallel mechanism is challenging due to the difficulty to obtain an accurate mathematical model and the fact that different sources of uncertainties ex...
Independently from artificial intelligence applications, an artificial neural network can be viewed as a powerful tool for function reconstruction. Previous papers used this property to model an impli...

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