Utilize AI to analyze application runtime data (e.g., rendering time, communication latency), obtain optimization suggestions (such as reducing component re-rendering, reusing hardware connections), ...
The challenge of resource allocation for UAV swarms in dynamic and uncertain electromagnetic environments has been ...
“I’m working on a Multi-Objective Bayesian Optimization (MOBO) problem involving a system with roughly 60 input parameters and around 30 performance evaluation metrics that we would ideally like to ...
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 ...
Abstract: Railway alignment design is a crucial but difficult task that should trade off many objective factors. Currently, although several Multi-objective Intelligent Alignment Optimization (M-IAO) ...
1 Guangzhou Institute of Building Science Group Co., Ltd., Guangzhou, Guangdong, China 2 Glenn Department of Civil Engineering, Clemson University, Clemson, SC, United States Modern seismic codes ...
In International Conference on Evolutionary Multi-objective Optimization. DOI: 10.1007/978-981-96-3538-2_9 [arXiv] The paper introduces an acquisition function for finding the Pareto front of a ...
Search optimization now requires combining traditional SEO with AI-focused GEO and answer-driven AEO strategies AI search usage continues to grow, with 10% of US consumers currently using generative ...
1 School of Mathematics and Statistics, Sichuan University of Science and Engineering, Zigong, China. 2 Institute of Computational Mathematics and Scientific/Engineering Computing, Chinese Academy of ...
Abstract: This paper addresses multi-objective optimization problems using conflict-averse multi-objective extremum seeking (CAMOES) for unknown static mapping. As for the traditional multi-objective ...
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