Modeling Extreme Traffic Loading On Bridges Using Kernel Density Estimators

Cathal Leahy; Eugene J. O'Brien; Bernard Enright

doi:10.21427/d7x81q

Modeling Extreme Traffic Loading On Bridges Using Kernel Density Estimators

Cathal Leahy, Eugene J. O'Brien, Bernard Enright

Technological University Dublin

Research output: Contribution to journal › Article › peer-review

Abstract

Kernel density estimators are a non-parametric method of estimating the probability density function of sample data. In this paper, the method is applied to find characteristic maximum daily truck weights on highway bridges. The results are then compared with the conventional approach

Original language	English
Pages (from-to)	439-446
Journal	Innovations on Bridges and Soil-Bridge Interaction
DOIs	https://doi.org/10.21427/d7x81q
Publication status	Published - 2011

Keywords

Kernel density estimators
non-parametric method
probability density function
sample data
characteristic maximum daily truck weights
highway bridges
conventional approach

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10.21427/d7x81qLicence: CC BY-NC-SA

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title = "Modeling Extreme Traffic Loading On Bridges Using Kernel Density Estimators",

abstract = "Kernel density estimators are a non-parametric method of estimating the probability density function of sample data. In this paper, the method is applied to find characteristic maximum daily truck weights on highway bridges. The results are then compared with the conventional approach",

keywords = "Kernel density estimators, non-parametric method, probability density function, sample data, characteristic maximum daily truck weights, highway bridges, conventional approach",

author = "Cathal Leahy and O'Brien, {Eugene J.} and Bernard Enright",

year = "2011",

doi = "10.21427/d7x81q",

language = "English",

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journal = "Innovations on Bridges and Soil-Bridge Interaction",

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AU - Leahy, Cathal

AU - O'Brien, Eugene J.

AU - Enright, Bernard

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N2 - Kernel density estimators are a non-parametric method of estimating the probability density function of sample data. In this paper, the method is applied to find characteristic maximum daily truck weights on highway bridges. The results are then compared with the conventional approach

AB - Kernel density estimators are a non-parametric method of estimating the probability density function of sample data. In this paper, the method is applied to find characteristic maximum daily truck weights on highway bridges. The results are then compared with the conventional approach

KW - Kernel density estimators

KW - non-parametric method

KW - probability density function

KW - sample data

KW - characteristic maximum daily truck weights

KW - highway bridges

KW - conventional approach

U2 - 10.21427/d7x81q

DO - 10.21427/d7x81q

M3 - Article

SP - 439

EP - 446

JO - Innovations on Bridges and Soil-Bridge Interaction

JF - Innovations on Bridges and Soil-Bridge Interaction

ER -

Modeling Extreme Traffic Loading On Bridges Using Kernel Density Estimators

Abstract

Keywords

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