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Modern configurable software systems need to learn models that correlate configuration and performance. However, when the system operates in dynamic environments, the workload variations, hardware ...
Abstract: Fuzzy recurrent stochastic configuration networks (FRSCNs) are a class of randomized neurofuzzy models that have shown success in modeling nonlinear dynamic systems. However, the data ...
This repository contains the implementation of Graph Neural Network (GNN)-based variational autoencoders used to learn representations of Multi-Access Point Coordination (MAPC) configurations in IEEE ...
ABSTRACT: The stochastic configuration network (SCN) is an incremental neural network with fast convergence, efficient learning and strong generalization ability, and is widely used in fields such as ...
ABSTRACT: The stochastic configuration network (SCN) is an incremental neural network with fast convergence, efficient learning and strong generalization ability, and is widely used in fields such as ...
Article Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to ...
VELIZY-VILLACOUBLAY, France--(BUSINESS WIRE)--Dassault Systèmes (Euronext Paris: FR0014003TT8, DSY.PA) today announced the launch of SOLIDWORKS SkillForce, its new global initiative to provide ...
Department of Science Education, College of Science and Technology Education, University of Science and Technology of Southern Philippines, Cagayan de Oro City, 9000 Philippines Science and ...
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