武警医学
武警醫學
무경의학
MEDICAL JOURNAL OF THE CHINESE PEOPLE'S ARMED POLICE FORCES
2014年
9期
916-920
,共5页
张桐硕%薄海%秦永生%彭朋
張桐碩%薄海%秦永生%彭朋
장동석%박해%진영생%팽붕
灰色关联分析%耐力素质%军校大学生%BP神经网络
灰色關聯分析%耐力素質%軍校大學生%BP神經網絡
회색관련분석%내력소질%군교대학생%BP신경망락
analysis,gray correlation%endurance performance%military academy students%BP neural network
目的:分析军校大学生5000 m跑成绩与相关运动生理指标的关系,为进一步科学安排训练、提高军人耐力素质提供理论依据。方法整群抽取58名某军校大学生,测试5000 m跑成绩,以及身体形态、心肺功能、速度素质和力量素质等四类共12项运动生理指标。建立灰色关联分析模型对采集的数据进行分析,运用BP神经网络模型验证评价效果。结果影响5000 m跑成绩的前5项主要因素依次为最大摄氧量(VO2max)、5000 m定量负荷心率、2000 m跑成绩、体脂百分比和肺活量指数。 VO2max和5000 m定量负荷心率能通过BP神经网络模型准确评价5000 m耐力素质。结论灰色关联分析模型筛选出的影响因素合理可信。应着重考虑安排有助于增强心肺功能和降低体脂百分比的训练项目,以减少训练的盲目性,提高5000 m耐力素质训练质量。
目的:分析軍校大學生5000 m跑成績與相關運動生理指標的關繫,為進一步科學安排訓練、提高軍人耐力素質提供理論依據。方法整群抽取58名某軍校大學生,測試5000 m跑成績,以及身體形態、心肺功能、速度素質和力量素質等四類共12項運動生理指標。建立灰色關聯分析模型對採集的數據進行分析,運用BP神經網絡模型驗證評價效果。結果影響5000 m跑成績的前5項主要因素依次為最大攝氧量(VO2max)、5000 m定量負荷心率、2000 m跑成績、體脂百分比和肺活量指數。 VO2max和5000 m定量負荷心率能通過BP神經網絡模型準確評價5000 m耐力素質。結論灰色關聯分析模型篩選齣的影響因素閤理可信。應著重攷慮安排有助于增彊心肺功能和降低體脂百分比的訓練項目,以減少訓練的盲目性,提高5000 m耐力素質訓練質量。
목적:분석군교대학생5000 m포성적여상관운동생리지표적관계,위진일보과학안배훈련、제고군인내력소질제공이론의거。방법정군추취58명모군교대학생,측시5000 m포성적,이급신체형태、심폐공능、속도소질화역량소질등사류공12항운동생리지표。건립회색관련분석모형대채집적수거진행분석,운용BP신경망락모형험증평개효과。결과영향5000 m포성적적전5항주요인소의차위최대섭양량(VO2max)、5000 m정량부하심솔、2000 m포성적、체지백분비화폐활량지수。 VO2max화5000 m정량부하심솔능통과BP신경망락모형준학평개5000 m내력소질。결론회색관련분석모형사선출적영향인소합리가신。응착중고필안배유조우증강심폐공능화강저체지백분비적훈련항목,이감소훈련적맹목성,제고5000 m내력소질훈련질량。
Objective To analyze the correlation between the performance of military academy students ’ 5000-meter running and their exercise physiology indicators associated with 5000-meter running so as to make further efforts to arrange training projects sci-entifically and provide a theoretical basis for military academy to improve the training quality of 5000-meter running .Methods 5000-meter running performance and 12 exercise physiological indexes grouped into four categories ( including anthropometry , cardiorespira-tory function , velocity fitness and strength fitness ) of 58 students from a military academy was measured by cluster sampling method . Gray correlation model was established to analyze the collected data .Then BP neural network model was used to verify the evaluation results.Results According to the order, the five main factors influencing the performance of 5000-meter running were VO2max, heart rate of 5000-meter running at fixed workload , performance of 2000-meter running , fat rate and FVC index .BP neural network model was able to accurately evaluate the endurance performance of 5000-meter running with VO2max and heart rate of 5000-meter running at fixed workload .Conclusion The factors screened by gray correlation model are reasonable and credible .Suggest military academy should consider arranging some training projects which contribute to improvement of cardiopulmonary function and drop of fat rate .By this way, the blindness of training is reduced so as to improve the training quality of 5000-meter running.