The future of urban green space might be written in code, according to research in the International Journal of ...

Abstract: Data-driven evolutionary algorithms (DDEAs) have achieved significant success in numerous real-world optimization problems, where exact objective functions and constraint functions do not ...

This study presents SynaptoGen, a differentiable extension of connectome models that links gene expression, protein-protein interaction probabilities, synaptic multiplicity, and synaptic weights, and ...

Science and Technology Daily, in collaboration with media partners and a panel of academicians from the Chinese Academy of Sciences and the Chinese Academy of Engineering, has selected the 2025 top 10 ...

The challenge of resource allocation for UAV swarms in dynamic and uncertain electromagnetic environments has been ...

In the field of multi-objective evolutionary optimization, prior studies have largely concentrated on the scalability of objective functions, with relatively less emphasis on the scalability of ...

Large language models (LLMs) leverage unsupervised learning to capture statistical patterns within vast amounts of text data. At the core of these models lies the Transformer architecture, which ...

This project solves the GECCO19 Traveling Thief Problem (TTP) using a Multi-objective Evolutionary Algorithm (MOEA) to optimize both travel time (TSP) and profit (KNP) with advanced crossover, ...