随着人类对动物或细菌等群体行为的深入研究,归纳出了许多基于生物智能的算法,这些算法能够解决一些无法在定义域内直接寻找到最优值的凸优化问题,是目前求解最优化问题的关键方法,但此类算法求解最优值过程中各有不足之处。本文针对黏...随着人类对动物或细菌等群体行为的深入研究,归纳出了许多基于生物智能的算法,这些算法能够解决一些无法在定义域内直接寻找到最优值的凸优化问题,是目前求解最优化问题的关键方法,但此类算法求解最优值过程中各有不足之处。本文针对黏菌优化算法(SMA)进行改进,引入权重更新和替换反正切函数为指数函数控制算法中关键参数这两种策略,在基准测试函数中得到结论,有效解决 SMA 算法在 3 个不同类型的基准函数中易陷入局部最优、收敛速度慢等瓶颈问题,提高了黏菌优化算法的收敛精度和速度,加强了全局搜索能力,在解决工程实际问题上,具有较高实际应用价值。展开更多
Background： Many studies examining individual-level correlates in youth utilize self-report rather than objective measures of physical activity （PA）. This utilization of self-report may result in associations that ...Background： Many studies examining individual-level correlates in youth utilize self-report rather than objective measures of physical activity （PA）. This utilization of self-report may result in associations that are not present when examining objectively measured PA. The present study investigates the relationship between hypothesized correlates of PA with objectively and subjectively measured PA. Methods： Participating children （n 232, 101 males, mean age - 12.3 years） provided a minimum of four monitored days of PA （via accelerometer） and completed a survey assessing moderate-to-vigorous physical activity （MVPA）, sport competence, appearance, enjoyment, and self-efficacy. Height and weight were measured and body mass index （BMI） was calculated. Results： Hierarchical regression models controlling for sex, race, and BMI Z-score showed that only sex and BMI Z-score were significant correlates of objective MVPA while only sex was a significant correlate of objective total PA. However, in a separate model examining the relationship with subjective MVPA, enjoyment of PA and self-efficacy for PA were the only significant correlates of self-reported PA. Conclusion： Measuring MVPA via self-report versus accelerometry produces considerably different results in a sample of young adolescents. Future studies should use caution when selecting outcome measures if the intent is to identify modifiable correlates of MVPA in youth.展开更多
文摘随着人类对动物或细菌等群体行为的深入研究,归纳出了许多基于生物智能的算法,这些算法能够解决一些无法在定义域内直接寻找到最优值的凸优化问题,是目前求解最优化问题的关键方法,但此类算法求解最优值过程中各有不足之处。本文针对黏菌优化算法(SMA)进行改进,引入权重更新和替换反正切函数为指数函数控制算法中关键参数这两种策略,在基准测试函数中得到结论,有效解决 SMA 算法在 3 个不同类型的基准函数中易陷入局部最优、收敛速度慢等瓶颈问题,提高了黏菌优化算法的收敛精度和速度,加强了全局搜索能力,在解决工程实际问题上,具有较高实际应用价值。
基金funded by the Centers for Disease Control and Prevention(K01-DP001126)
文摘Background： Many studies examining individual-level correlates in youth utilize self-report rather than objective measures of physical activity （PA）. This utilization of self-report may result in associations that are not present when examining objectively measured PA. The present study investigates the relationship between hypothesized correlates of PA with objectively and subjectively measured PA. Methods： Participating children （n 232, 101 males, mean age - 12.3 years） provided a minimum of four monitored days of PA （via accelerometer） and completed a survey assessing moderate-to-vigorous physical activity （MVPA）, sport competence, appearance, enjoyment, and self-efficacy. Height and weight were measured and body mass index （BMI） was calculated. Results： Hierarchical regression models controlling for sex, race, and BMI Z-score showed that only sex and BMI Z-score were significant correlates of objective MVPA while only sex was a significant correlate of objective total PA. However, in a separate model examining the relationship with subjective MVPA, enjoyment of PA and self-efficacy for PA were the only significant correlates of self-reported PA. Conclusion： Measuring MVPA via self-report versus accelerometry produces considerably different results in a sample of young adolescents. Future studies should use caution when selecting outcome measures if the intent is to identify modifiable correlates of MVPA in youth.
