Pattern recognition of seismogenic nodes using Kohonen self-organizing map: example in west and south west of Alborz region in Iran

Allamehzadeh, Mostafa; Durudi, Soma; Mahshadnia, Leila

doi:10.1007/s11589-017-0190-7

Cited by 2 publications

(1 citation statement)

References 30 publications

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“…where λ is the power exponent of the membership function r, Z = ðz 1 , z 2 ,⋯,z c Þ is the cluster center of a given input sample, and R is a fuzzy c partition of the input sample Y. The above formula is the core optimization goal of Kohonen neural network algorithm [13,14].…”

Section: Application Of Kohonen Neural Network In Sports Clustermentioning

confidence: 99%

Application of Kohonen Neural Network in Sports Cluster

You-wen

2022

Wireless Communications and Mobile Computing

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People’s physical fitness is directly linked to the national physique of a country. It is an important analysis indicator of the country’s comprehensive national strength and economic level. Moreover, students’ physical and mental health is in a stage of rapid development. Their physical health is not only directly related to their study and life at this stage but it will also have a profound impact on the physical level, health status, and work ability of adults. Starting from the cluster analysis of sports, this article explores the communication effects of sports, communication strategies, and the relationship between sports and the development of users’ healthy habits by defining concepts and types and combining quantitative and qualitative analysis. Study the relationship and then analyze whether sports applications bring people the effect of promoting healthy behavior. This article retrieved documents about the application of Kohonen neural network in sports cluster analysis in domestic literature databases such as Weipu, Wanfang data, and CNKI. A total of 144 documents were retrieved from the database, and the retrieved documents were collected for sports activities. The study of class analysis can avoid human subjective factors and obtain clustering results quickly and objectively, thus providing an ideal clustering method for comprehensive evaluation of sports. The experiment proves the cluster analysis of the impact of sports on people’s physical fitness, the heterogeneity test results are 0% (boys) and 3% (girls), it is believed that there is no statistical heterogeneity in the physical fitness of middle school boys in each study, and P < 0.001 , indicating that the influence of sports on people’s physical fitness is significantly different between the experimental group and the control group. This shows that the application of Kohonen neural network clustering analysis method has great practical value for comprehensively evaluating people’s physical functions and physical fitness. It is an objective, reasonable, effective, and rapid quantitative evaluation method.

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Section: Application Of Kohonen Neural Network In Sports Clustermentioning

confidence: 99%