After 30 months of fast-paced innovation in quantum algorithms, six research groups are hoping to hit paydirt. But there can ...

To address these shortcomings, we introduce SymPcNSGA-Testing (Symbolic execution, Path clustering and NSGA-II Testing), a ...

The simulator takes into account forecasted demand in each region, transportation costs, and the operational capacity of each warehouse.

The Massachusetts Institute of Technology (MIT) Center for Transportation & Logistics and Mecalux have developed an artificial intelligence-based simulator designed to optimise inventory distribution ...

Abstract: Autonomous vehicles are becoming a reality, yet it is only truly autonomous with a strong model. The system can be trained by implementing a genetic algorithm as an optimizer in its ...

Abstract: The increasing demand for sustainable energy has led to intensified research on bioethanol production from renewable sources. Microalgae, specifically Chlorella vulgaris and Spirulina ...

Are Machine Learning (ML) algorithms superior to traditional econometric models for GDP nowcasting in a time series setting? Based on our evaluation of all models from both classes ever used in ...

Using data from ten healthy adults, we trained a Gradient Boosting (GB) surrogate model to predict normalized metabolic cost as a function of Peak Magnitude and End ...

The consortium running the European Space Agency's (ESA) Euclid mission has published the most extensive simulation of the cosmos to date. The modeling was based on algorithms developed by UZH ...

Is this real life? Is this just fantasy? A growing number of scientists are suggesting that the idea that we are all living in a simulation may not be completely far-fetched. Simulation theory is the ...

The operation of the power grid is closely related to meteorological disasters. Changes in meteorological conditions may have an impact on the operation and stability of the power system, leading to ...