Parametric distance functions vs. nonparametric neural networks for estimating road travel distances

DOI10.1016/0377-2217(96)00045-8zbMath0912.90114OpenAlexW2059938223MaRDI QIDQ1268152

K. Appert

Publication date: 18 October 1998

Published in: European Journal of Operational Research (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0377-2217(96)00045-8

zbMATH Keywords

neural networksnonparametric regressionlocationregressionmulti-layer perceptronsroad transportationdistance estimatorsnonparametric approaches

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Transportation, logistics and supply chain management (90B06)

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Uses Software

• MINOS

Cites Work

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• Probabilistic \(l_ p\) distances in location models
• Estimating road distances by mathematical functions
• Consistent nonparametric regression. Discussion
• Multilayer feedforward networks are universal approximators
• Using Block Norms for Location Modeling
• Mathematical Models of Road Travel Distances
• Technical Note—A New Norm for Measuring Distance Which Yields Linear Location Problems
• A New Distance Function for Modeling Travel Distances in a Transportation Network
• Confidence Intervals for l_k,p,θ Distances
• Modelling Inter-city Road Distances by Mathematical Functions

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