Path loss prediction in urban environment using learning machines and dimensionality reduction techniques

DOI10.1007/s10287-010-0121-8zbMath1225.90017OpenAlexW2119281476MaRDI QIDQ645503

Francesco Rinaldi, Mauro Piacentini

Publication date: 15 November 2011

Published in: Computational Management Science (Search for Journal in Brave)

Full work available at URL: http://www.dis.uniroma1.it/~bibdis/RePEc/aeg/wpaper/2009-11.pdf

zbMATH Keywords

dimensionality reduction techniqueslearning machinespath loss prediction

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Communication networks in operations research (90B18) Approximation methods and heuristics in mathematical programming (90C59)

Uses Software

• L-BFGS-B
• LBFGS-B

Cites Work

• Occam's razor
• Nonmonotone globalization techniques for the Barzilai-Borwein gradient method
• Algorithm 778: L-BFGS-B
• A Limited Memory Algorithm for Bound Constrained Optimization
• Learning representations by back-propagating errors
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