In recent years, deep learning technologies have received huge attention and interest in the field of high-performance material design. This is primarily because deep learning algorithms in nature have huge advantages over ...

This work applies connectionist neural network learning techniques and symbolic machine learning techniques to the problem of short-term electric load forecasting. The short-term electric load forecasting problem considered ...

We introduce recurrent collective classification (RCC), a variant of ICA analogous to recurrent neural network prediction. RCC accommodates any differentiable local classifier and relational feature functions. We provide ...

With technology and computers becoming more and more sophisticated and readily available, cars have followed suit by integrating more and more microcontrollers to handle tasks ranging from controlling the radio to the ...

Reynolds-Averaged Navier-Stokes (RANS) simulations are widely used for engineering design and analysis involving turbulent flows. In RANS simulations, the Reynolds stress needs closure models and the existing models have ...

Computational fluid dynamics (CFD) has been widely used to simulate turbulent flows. Although an increased availability of computational resources has enabled high-fidelity simulations (e.g. large eddy simulation and direct ...

Sociotechnical systems (STSs) rely on the collaboration between humans and autonomous decision-making units to fulfill their objectives. Highly intertwined social and technical contextual factors influence the collaboration ...

Polyolefins are one of the most widely used commodity polymers with applications in films, packaging and automotive industry. The modeling of polymerization processes producing polyolefins, including high-density polyethylene ...

The study of information extraction and knowledge exploration in the urban environment is gaining popularity. Ubiquitous sensors and a plethora of statistical reports provide an immense amount of heterogeneous urban data, ...

As power system grids continue to grow in order to support an increasing energy demand, the system's behavior accordingly evolves, continuing to challenge designs for maintaining security. It has become apparent in the ...