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 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 ...

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 ...

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 ...

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 ...

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 ...

What makes this development especially revolutionary in battery research is the integration of physics-informed principles into neural networks. Traditional neural networks are data-driven models that ...