Traditional time-series forecasting models are ill-equipped to handle the dynamic and event- driven nature of Q-commerce ...

In this rapidly growing digital era, generative AI's power reshapes the art of building more innovative machine learning ...

Abstract: Dispatching rules are most commonly used to solve scheduling problems under dynamic conditions ... In previous research, genetic programming has been the most commonly used method for ...

Abstract: This paper presents a development of an improved genetic algorithm (IGA) and its application to a least-cost generation expansion planning (GEP) problem. Least-cost GEP problem is concerned ...

Endogenous intracellular allosteric modulators of GPCRs remain largely unexplored, with limited binding and phenotype data available. This gap arises from the lack of robust computational methods for ...

Google's next-generation Tensor processing hardware will also benefit from AlphaEvolve. DeepMind reports that the AI created ...

Quantum computing has potentially transformative capabilities for analyzing agricultural biological systems with ...

Dynamic traits vary considerably among individuals. Similarly, the patterns of genetic control that they are under vary over a given time course. Figure 1 illustrates four representative patterns ...

Explore how Microsoft CEO Satya Nadella envisions AI reshaping healthcare, climate action, and the global economy responsibly ...

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