1–20 von 33 Ergebnissen
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    Investigation of work zone crash casualty patterns using association rules

    Weng, Jinxian / Zhu, Jia-Zheng / Yan, Xuedong et al. | Elsevier | 2016
    Schlagwörter: Data mining , Data visualization

    Application of association rules mining algorithm for hazardous materials transportation crashes on expressway

    Hong, Jungyeol / Tamakloe, Reuben / Park, Dongjoo | Elsevier | 2020
    Schlagwörter: association rules mining , data mining

    Construction accident narrative classification: An evaluation of text mining techniques

    Goh, Yang Miang / Ubeynarayana, C.U. | Elsevier | 2017
    Schlagwörter: Data mining , Text mining

    Development and evaluation of a Naïve Bayesian model for coding causation of workers’ compensation claims

    Bertke, S.J. / Meyers, A.R. / Wurzelbacher, S.J. et al. | Elsevier | 2012
    Schlagwörter: Data-mining , Text-mining

    Using data mining techniques to predict the severity of bicycle crashes

    Prati, Gabriele / Pietrantoni, Luca / Fraboni, Federico | Elsevier | 2017
    Schlagwörter: Data mining

    Rule discovery to identify patterns contributing to overrepresentation and severity of run-off-the-road crashes

    Montella, Alfonso / Mauriello, Filomena / Pernetti, Mariano et al. | Elsevier | 2021
    Schlagwörter: Severe and fatal crashes , Data mining

    Applying data mining techniques to explore factors contributing to occupational injuries in Taiwan's construction industry

    Cheng, Ching-Wu / Leu, Sou-Sen / Cheng, Ying-Mei et al. | Elsevier | 2011
    Schlagwörter: Data mining , Data analysis

    Analysis of traffic injury severity: An application of non-parametric classification tree techniques

    Chang, Li-Yen / Wang, Hsiu-Wen | Elsevier | 2006
    Schlagwörter: Data mining , Classification and regression trees (CART)

    A method for simplifying the analysis of traffic accidents injury severity on two-lane highways using Bayesian networks

    Mujalli, Randa Oqab / de Oña, Juan | Elsevier | 2011
    Schlagwörter: Data mining

    Review on big data applications in safety research of intelligent transportation systems and connected/automated vehicles

    Lian, Yanqi / Zhang, Guoqing / Lee, Jaeyoung et al. | Elsevier | 2020
    Schlagwörter: Big Data , Data mining , Connected and automated vehicles

    Application of a model-based recursive partitioning algorithm to predict crash frequency

    Tang, Houjun / Donnell, Eric T. | Elsevier | 2019
    Schlagwörter: Data mining

    Fatal pedestrian crashes at intersections: Trend mining using association rules

    Das, Subasish / Tamakloe, Reuben / Zubaidi, Hamsa et al. | Elsevier | 2021
    Schlagwörter: Data mining

    A data mining approach to deriving safety policy implications for taxi drivers

    Park, Jiwon / Lee, Seolyoung / Oh, Cheol et al. | Elsevier | 2020
    Schlagwörter: Data mining

    A study on the cyclist head kinematic responses in electric-bicycle-to-car accidents using decision-tree model

    Gao, Wenrui / Bai, Zhonghao / Zhu, Feng et al. | Elsevier | 2021
    Schlagwörter: Data mining

    Analysis of the severity of vehicle-bicycle crashes with data mining techniques

    Zhu, Siying | Elsevier | 2020
    Schlagwörter: Integrated data mining framework

    Neck injury mechanisms in train collisions: Dynamic analysis and data mining of the driver impact injury

    Hou, Lin / Peng, Yong / Sun, Dong | Elsevier | 2020
    Schlagwörter: Data mining

    Understanding spatial concentrations of road accidents using frequent item sets

    Geurts, Karolien / Thomas, Isabelle / Wets, Geert | Elsevier | 2005
    Schlagwörter: Data Mining

    Using trajectory-level SHRP2 naturalistic driving data for investigating driver lane-keeping ability in fog: An association rules mining approach

    Das, Anik / Ahmed, Mohamed M. / Ghasemzadeh, Ali | Elsevier | 2019
    Schlagwörter: Data mining techniques , Association rules mining

    Prioritizing Highway Safety Manual’s crash prediction variables using boosted regression trees

    Saha, Dibakar / Alluri, Priyanka / Gan, Albert | Elsevier | 2015
    Schlagwörter: Data mining