Abstract: This paper presents a novel neural network-based optimization framework, NNDE, to solve the traveling salesman problem (TSP). The core idea is to use a radial basis function network (RBFN) ...
Abstract: The circuits of high-power vacuum electron devices (HPVEDs) typically possess complex topologies that are crucial for efficiently converting electron beam energy to microwave energy. Due to ...
Researchers from Chiba University have developed a lightweight peer-selection algorithm that significantly reduces data propagation delays without increasing resource usage on internet of things (IoT) ...
It shows the schematic of the physics-informed neural network algorithm for pricing European options under the Heston model. The market price of risk is taken to be λ=0. Automatic differentiation is ...
When Fei-Fei Li arrived in Princeton in January 2007 as an assistant professor, she was assigned an office on the second floor of the computer science building. Her neighbor was Christiane Fellbaum.
This repository provides implementation for SNBO (Scalable Neural Network-based Blackbox Optimization) — a novel method for efficient blackbox optimization using neural networks. It also includes code ...
Artificial neural networks are machine learning models that have been applied to various genomic problems, with the ability to learn non-linear relationships and model high-dimensional data. These ...
ABSTRACT: Supply chain networks, which integrate nodes such as suppliers, manufacturers, and retailers to achieve efficient coordination and allocation of resources, serve as a critical component in ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results