These open-source MMM tools solve different measurement problems, from budget optimization to forecasting and preprocessing.

A team of researchers from the Shanghai Institute of Applied Physics, Chinese Academy of Sciences, has developed an ...

This study from MIT explores eye evolution through AI simulations, uncovering how different tasks shape visual systems and ...

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

ABSTRACT: This note examines the utility of pseudorandom variables (prv) in Global Search and Optimization (GSO) using Central Force Optimization (CFO) as an example. Most GSO metaheuristics are ...

Abstract: Evolutionary multi-task optimization is an emerging research topic in the field of evolutionary computation. It aims to achieve simultaneous optimization of different tasks by dynamically ...

The challenge of resource allocation for UAV swarms in dynamic and uncertain electromagnetic environments has been investigated for years. In a recent breakthrough published in the Chinese Journal of ...

EvoToolkit is a Python library that leverages Large Language Models (LLMs) to evolve solutions for optimization problems. It combines the power of evolutionary algorithms with LLM-based solution ...

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 ...

Tourism development in emerging destinations requires balancing economic benefits with ecological sustainability. In this study, we investigate the case of multi-attraction tourism planning in Qujing ...

High-dimensional data often contain noisy and redundant features, posing challenges for accurate and efficient feature selection. To address this, a dynamic multitask learning framework is proposed, ...