Predicting Construction Workers’ Unsafe-behaving Intentions Using Machine Learning Algorithms and Basic Taxonomy of Personality
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Predicting Construction Workers’ Unsafe-behaving Intentions Using Machine Learning Algorithms and Basic Taxonomy of Personality
Summary
Predicting Construction Workers’ Unsafe-behaving Intentions Using Machine Learning Algorithms and Basic Taxonomy of Personality is a doctoral thesis[1].
Key Facts
- Predicting Construction Workers’ Unsafe-behaving Intentions Using Machine Learning Algorithms and Basic Taxonomy of Personality authored Yifan Gao[2].
- Predicting Construction Workers’ Unsafe-behaving Intentions Using Machine Learning Algorithms and Basic Taxonomy of Personality's instance of is recorded as doctoral thesis[3].
- Predicting Construction Workers’ Unsafe-behaving Intentions Using Machine Learning Algorithms and Basic Taxonomy of Personality's publisher is recorded as ResearchSpace@Auckland[4].
- Predicting Construction Workers’ Unsafe-behaving Intentions Using Machine Learning Algorithms and Basic Taxonomy of Personality's copyright license is recorded as Creative Commons Attribution-NonCommercial-ShareAlike 3.0 New Zealand[5].
- Predicting Construction Workers’ Unsafe-behaving Intentions Using Machine Learning Algorithms and Basic Taxonomy of Personality's country of origin is recorded as New Zealand[6].
- Predicting Construction Workers’ Unsafe-behaving Intentions Using Machine Learning Algorithms and Basic Taxonomy of Personality's publication date is recorded as +2020-00-00T00:00:00Z[7].
- Predicting Construction Workers’ Unsafe-behaving Intentions Using Machine Learning Algorithms and Basic Taxonomy of Personality's main subject is recorded as civil engineering studies[8].
- Predicting Construction Workers’ Unsafe-behaving Intentions Using Machine Learning Algorithms and Basic Taxonomy of Personality's work available at URL is recorded as https://researchspace.auckland.ac.nz/handle/2292/52531[9].
- Predicting Construction Workers’ Unsafe-behaving Intentions Using Machine Learning Algorithms and Basic Taxonomy of Personality's Handle ID is recorded as 2292/52531[10].
- Predicting Construction Workers’ Unsafe-behaving Intentions Using Machine Learning Algorithms and Basic Taxonomy of Personality's title is recorded as Predicting Construction Workers’ Unsafe-behaving Intentions Using Machine Learning Algorithms and Basic Taxonomy of Personality[11].
- Predicting Construction Workers’ Unsafe-behaving Intentions Using Machine Learning Algorithms and Basic Taxonomy of Personality's copyright holder is recorded as Yifan Gao[12].
- Predicting Construction Workers’ Unsafe-behaving Intentions Using Machine Learning Algorithms and Basic Taxonomy of Personality's thesis submitted to is recorded as University of Auckland[13].
- Predicting Construction Workers’ Unsafe-behaving Intentions Using Machine Learning Algorithms and Basic Taxonomy of Personality's on focus list of Wikimedia project is recorded as NZThesisProject[14].
- Predicting Construction Workers’ Unsafe-behaving Intentions Using Machine Learning Algorithms and Basic Taxonomy of Personality's copyright status is recorded as copyrighted[15].
- Predicting Construction Workers’ Unsafe-behaving Intentions Using Machine Learning Algorithms and Basic Taxonomy of Personality's online access status is recorded as open access[16].
- Predicting Construction Workers’ Unsafe-behaving Intentions Using Machine Learning Algorithms and Basic Taxonomy of Personality's thesis committee member is recorded as Vicente A González[17].
- Predicting Construction Workers’ Unsafe-behaving Intentions Using Machine Learning Algorithms and Basic Taxonomy of Personality's thesis committee member is recorded as Tak Wing Yiu[18].
- Predicting Construction Workers’ Unsafe-behaving Intentions Using Machine Learning Algorithms and Basic Taxonomy of Personality's thesis committee member is recorded as Yang Zou[19].
Body
Designation and Status
Predicting Construction Workers’ Unsafe-behaving Intentions Using Machine Learning Algorithms and Basic Taxonomy of Personality's instance of is recorded as doctoral thesis[3].