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Application of Data Mining Technology for the Effects of Modern Pentathlon on the Prevention of Urban White-collar workers’ Occupational Disease

Wenxin Xu, Jiwei Yao


Data Mining is a process that extracts information and knowledge which is contained, unknown by people but potentially useful from lots of incomplete, noisy, fuzzy and random data of practical application in order to make people discover useful new laws and new concepts as well as improve researches’ profound comprehension, recognition and application of a large number of raw data. As the modern pentathlon is of so great exercise value that it is popular with people in modern times. Based on the data mining technology, this thesis integrates neural network, Decision Tree Model (DTM), ID3 algorithm and specifically analyzes the effects of the modern pentathlon on the prevention of white-collar workers’ common occupational disease, In addition, it used the neural network and the DT model to carry out quantitative analyses of the effects of the modern pentathlon on the prevention of the occupational disease.


Data mining technology, neural network, ID3 algorithm, Decision Tree Model, Modern pentathlon, Occupational disease.

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