Predicting Construction Workers’ Unsafe-behaving Intentions Using Machine Learning Algorithms and Basic Taxonomy of Personality
0 sources
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 was published by 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 was released on 2020[7].
- Predicting Construction Workers’ Unsafe-behaving Intentions Using Machine Learning Algorithms and Basic Taxonomy of Personality's main subject is 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 title is recorded as Predicting Construction Workers’ Unsafe-behaving Intentions Using Machine Learning Algorithms and Basic Taxonomy of Personality[10].
- Predicting Construction Workers’ Unsafe-behaving Intentions Using Machine Learning Algorithms and Basic Taxonomy of Personality's copyright holder is recorded as Yifan Gao[11].
- 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[12].
- 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[13].
- Predicting Construction Workers’ Unsafe-behaving Intentions Using Machine Learning Algorithms and Basic Taxonomy of Personality's copyright status is recorded as copyrighted[14].
- Predicting Construction Workers’ Unsafe-behaving Intentions Using Machine Learning Algorithms and Basic Taxonomy of Personality's online access status is recorded as open access[15].
- 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[16].
- 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[17].
- Predicting Construction Workers’ Unsafe-behaving Intentions Using Machine Learning Algorithms and Basic Taxonomy of Personality's thesis committee member is recorded as Yang Zou[18].
- Predicting Construction Workers’ Unsafe-behaving Intentions Using Machine Learning Algorithms and Basic Taxonomy of Personality's thesis submitted for degree is recorded as Doctor of Philosophy[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].