A linear-time crystal-growth algorithm for discretization of continuum approximation

Fan, Hongqiang; Liu, Yun; Li, Xiaopeng

doi:10.1016/j.tre.2022.102715

Cited by 1 publication

(2 citation statements)

References 27 publications

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“…If the best value of college students' physical exercise habits is still not obtained after iterative calculation, the search for this influencing factor will be abandoned and other influencing factors will be analyzed Fan et al [ 10 ]. At the same time, according to formula ( 4 ), new influencing factors are randomly obtained here for the next judgment.…”

Section: Concepts Related To the Continuous Discrete Algorithmmentioning

confidence: 99%

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Analysis of Influencing Factors of College Students’ Physical Exercise Habits Based on the Continuous Discrete Algorithm

Zhang

Jiang

Shi

et al. 2022

Journal of Environmental and Public Health

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At present, college students give great importance to their physical training, but their physical habits are poor and they cannot exercise regularly. In view of the influencing factors in the habit formation of physical exercise, this paper puts forward a continuous discrete algorithm to provide students with a scientific and reasonable habit formation scheme. First, the data of college students’ physical exercise habits are collected, and the data are cleaned and continuously analyzed to initially form a habit formation data set; Then, the information gain and clustering thought in the discrete algorithm are used to judge the data change, and the ordered relationship among the factors is obtained. Finally, in judging the influence degree of each factor, we find out the final influencing factors. MATLAB simulation shows that the continuous discrete algorithm can accurately analyze the problem of physical exercise habit formation and sort the influencing factors, with an accuracy rate of 90% and a calculation time of less than 19 minutes, which is significantly better than the original discrete algorithm.

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Section: Concepts Related To the Continuous Discrete Algorithmmentioning

confidence: 99%

“…Moreover, the peak value of Cauthy (0, 1) is smaller than that of Gauss (0, 1), which weakens the influence of other factors. Based on the above analysis, the judgment formula of physical exercise adjustment factors can be transformed into formula (10).…”

Section: Continuous Discrete Algorithmmentioning

confidence: 99%