Fig. 1 shows the mapping of points from the training sample in the coordinates of the two main features – u1 and u2. The color of the point corresponds to the class (red – 0, aqua – 1). From the ...

In recent years, predictive technologies for volcanic eruptions have advanced significantly, particularly with the implementation of neural networks. These advanced algorithms are capable of ...

Recent advances in neural network methodologies have significantly reshaped the fields of electrical tomography and moisture analysis. By integrating artificial neural networks (ANNs) for both image ...

Over the last 10 years, neural networks have been increasingly applied to various areas of finance. Neural networks are more often applied on the assets side than on the liabilities side of the ...

Earth Scientists have used machine learning for at least three decades and the applications span is large, from remote sensing to analysis of well log data, among many others. Although machine ...

Artificial digital neural network concept. Neural network software enables the implementation, deployment and training of artificial neural networks. These networks are designed to mimic the behavior ...

While power tools and libraries, such as Apache Spark and Intel’s Trusted Analytics Platform, make it possible to quickly design, implement, train, and test neural network applications, it is the ...

Want smarter insights in your inbox? Sign up for our weekly newsletters to get only what matters to enterprise AI, data, and security leaders. Subscribe Now Neural networks are the backbone of ...