In this paper, finite element based neural network is developed. The purpose is to solve differential equation and inverse problem of differential equation. Inverse problem of differential equation is ...

This paper introduces a novel approach for predicting gasoline engine torque using a neural network model based on the Levenberg-Marquardt algorithm (LMA). The model generates an engine torque map by ...

When someone starts a new job, early training may involve shadowing a more experienced worker and observing what they do ...

Many existing methods for exploring the link between neural activity ... with a multisection neural network architecture and training approach." The researchers trained their RNN-based model using a ...

In both open-source datasets and a live urban testbed in Beijing, the algorithm demonstrated up to 21.09% improvement in positioning accuracy compared to traditional models, and outperformed the ...

The train, carrying 55 containers filled with goods such as LCD displays and refrigerators valued at nearly 20 million yuan ($2.75 million), is bound for Moscow and expected to arrive in 17 days.

This book covers the following exciting features: Understand perceptrons and how to implement them in C# Learn how to train and visualize a neural network using cognitive services Perform image ...

By default, if you use mot17.py as your dataset file, the Dataset class will prepare for both the MOT17 and CrowdHuman datasets. If you want only to use a single dataset, you may choose one of the ...

The study’s authors note that small neural networks — simplified versions of the neural networks typically used in commercial ...

To effectively monitor and control the fermentation process, an accurate real-time measurement of important variables is necessary. However, given the complexity of microbial fermentation and the ...