An important aspect in software engineering is the ability to distinguish between premature, unnecessary, and necessary ...
The study addresses heterogeneous UAV cooperative task assignment under complex constraints via an energy learning ...
Researchers at Google Cloud and UCLA have proposed a new reinforcement learning framework that significantly improves the ability of language models to learn very challenging multi-step reasoning ...
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: This article points out the seriousness and urgency of urban traffic congestion, and the shortcomings of existing research in solving this problem. In order to make up for these shortcomings ...
This paper investigates the application of machine learning techniques to optimize complex spray-drying operations in manufacturing environments. Using a mixed-methods approach that combines ...
Traditional path planning algorithms often face problems such as local optimum traps and low monitoring efficiency in agricultural UAV operations, making it difficult to meet the operational ...
A new algorithm helps topology optimizers skip unnecessary iterations, making optimization and design faster, more stable and more useful. PROVIDENCE, R.I. [Brown University] — With the rise of 3D ...
Abstract: This paper introduces a new discrete StarFish Optimization Algorithm (D-SFOA) to solve a complex discrete Symmetric Travelling Salesman Problem (STSP). The discrete SFOA algorithm is ...
The best CRM article on Page 1 might lose to a single paragraph buried on Page 3. That’s how AI search works now, and it’s why traditional SEO strategies are failing businesses that should be winning.
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