FatemehHPayamDAhmadH.Assessing the performance of decision tree and neural network models in mapping soil properties. J Mountain Sci2019;
16: 1833–1847.
2.
SantosOC.Artificial intelligence in psychomotor learning: modeling human motion from inertial sensor data. Int J Artif Intell Tools2019;
28: 1940006.
3.
CagatayD.Examination of studying approaches of students at school of physical education and sports in terms of different variables. J Educ Train Stud2017;
5: 252.
4.
ZhangYXFengW.Decision tree analysis in determinants of elderly visits in poor rural areas. Beijing Da Xue Xue Bao Yi Xue Ban2018;
50: 450–456.
5.
HanQZhangXShenW.Application of support vector machine based on decision tree feature extraction in lithology classification. Jilin DaxueXuebao (DiqiuKexueBan)/J Jilin Univ (Earth Sci Ed)2019;
49: 611–620.
6.
GuoqiangLXuguangLJiangW.A limb-based graphical model for human pose estimation. IEEE Trans Syst Man Cybernet Syst2018;
48: 1080–1092.
7.
LiY-LZhangH-JGuoX-T.Modeling and analysis of higher schools massive sports data based on cloud computing. Int J Electr Eng Educ. Epub ahead of print 1 October 2019. DOI: 10.1177/0020720919879388.
8.
BrendonH.A simulation pedagogical approach to engaging generalist pre-service teachers in physical education online: the Gopro trial 1.0. Austr J Teach Educ2017;
42: 84102.
9.
SunyoungKSeungaeK.The study on the application of virtual reality in adapted physical education. Cluster Comput2019;
22: 1–5.
10.
WangQLuP.Research on application of artificial intelligence in computer network technology. Int J Patt Recogn Artif Intell2019;
33: 1959015.
11.
PedroASánchezMDianaA.Foreword of the special issue on motivation in physical education, sport and physical activity and health. J Hum Kinet2017;
59: 3–4.
12.
LytleR.Physical education for children with moderate to severe. Adapt Phys Activ2018;
35: 243–244.
13.
EkblomBakEEkblomÖAnderssonG.Physical education and leisure-time physical activity in youth are both important for adulthood activity, physical performance, and health. J Phys Activity Health2018;
15: 661–670.
14.
KaissarY.The effectiveness of physical models in teaching anatomy: a meta-analysis of comparative studies. Adv Health Sci Educ2015;
21: 1–13.
15.
EkinciSZeynelgilHLale; DemirorenA.A didactic procedure for transient stability simulation of a multi-machine power system utilizing SIMULINK. Int J Electr Eng Educ2016;
53: 54–71.
16.
WangCGaoN.Study of the plural evaluation indicators system and evaluation model in physical education teaching in institution of higher learning. J Comput Theor Nanosci2017;
14: 177–181.
17.
Bergen CWV and Bressler MS. Academe’s unspoken ethical dilemma: author inflation in higher education. Res Higher Educ J 2017; 32: 1–17.
18.
KondratiukOSKorshunMMGarkavyiSI, et al.
Hygienic assessment of different forms of physical education lessons organization in primary school. Wiad Lek2018;
71: 542–545.
19.
Bravo MM, Cummins KM and Nessler JA. Heart rate responses of high school students participating in surfing physical education. J Strength Condition Res 2016; 30(6): 1721–1726.
20.
Sushil S, Chaurasia A and Frieda R. From big data to big impact: Analytics for teaching and learning in higher education. Industrial & Commercial Training 2017; 49: 321–328.
21.
Santos P, Carvalho Pereira A and Gervásio H. Assessment of health and comfort criteria in a life cycle social context: application to buildings for higher education. Build Environ 2017; 123: 625–648.
22.
CédricRDenisP.Exploring situational interest sources in the French physical education context. Eur Phys Educ Rev2018;
24: 3–20.
23.
Ellen N, Veronika R and Ellen DA. Participation in school and physical education in juvenile idiopathic arthritis in a Nordic long-term cohort study. Pediatr Rheumatol 2019; 17: 1–10.
24.
KrishnarajNElhosenyMLydiaEL, et al. An efficient radix trie‐based semantic visual indexing model for large‐scale image retrieval in cloud environment. Softw Pract Exp. Epub ahead of print 14 April 2020. DOI: 10.1002/spe.2834.
25.
GaoZXuanHZZhangH, et al.
Adaptive fusion and category-level dictionary learning model for multi-view human action recognition. IEEE Internet Things J2019;
6: 9280–9293.
26.
IvZSongH. Trust mechanism of multimedia network. ACM Trans Multimedia Comput, Commun Appl 2020. Aailable at: https://doi.org/10.1145/3391296.
27.
Abdel-BassetMMohamedMElhosenyM, et al.
Cosine similarity measures of bipolar neutrosophic set for diagnosis of bipolar disorder diseases. Artif Intell Med 5 October 2019;
101: 101735.
28.
ZhangLShiH-MZengX-H, et al.
Theoretical and experimental study on the transmission loss of a side outlet muffler. Shock Vib2020; 1: 1–8.