2021
DOI: 10.53623/csue.v1i1.28
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Investigating the Use of Active Transportation Modes Among University Employees Through an Advanced Decision Tree Algorithm

Abstract: Now more than ever, the health and economic benefits of active transportation (AT) are evident and several planning efforts and programs are particularly targeted at improving active transportation options for different populations, such as students and seniors. Administrative employees at universities received less attention in the literature than other population groups.This population spends a lot of time doing sedentary activities and behaviors during their working time. Thus, the present study used a C5 d… Show more

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Cited by 7 publications
(4 citation statements)
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“…Most of the solutions mentioned above, however, rely heavily on pre-existing assumptions. Machine learning (ML) techniques have more flexibility than traditional statistical models in that they can analyse noisy data, outliers, and missing data, without or with minimal previous assumptions about inputs [12][13][14][15][16][17][18]. In addition, ML methods are notable instances of data-driven techniques that strive to improve the efficiency and precision of accident data processing and forecasting.…”
Section: Introductionmentioning
confidence: 99%
“…Most of the solutions mentioned above, however, rely heavily on pre-existing assumptions. Machine learning (ML) techniques have more flexibility than traditional statistical models in that they can analyse noisy data, outliers, and missing data, without or with minimal previous assumptions about inputs [12][13][14][15][16][17][18]. In addition, ML methods are notable instances of data-driven techniques that strive to improve the efficiency and precision of accident data processing and forecasting.…”
Section: Introductionmentioning
confidence: 99%
“…In the application of the algorithm, the training sample set is input, the decision attributes are output, and the decision tree is established with the training sample set as the root node (Aghaabbasi et al, 2021). If all samples belong to the same category, record them as leaf nodes and mark the category.…”
Section: Improvement Of Decision Tree Algorithmmentioning
confidence: 99%
“…In addition, the tolerable walking travel time of pedestrians to transit stations can be increased if the walkability at the micro-level is improved [107]. Street elements, such as lighting, seating areas, trees, and width of sidewalk, may increase the distances people are willing to walk [22,108,109].…”
Section: Conclusion and Recommendationsmentioning
confidence: 99%