Study on Factors Influencing Physical Health Based on the SOM Network

2016 ◽  
Vol 13 (10) ◽  
pp. 6850-6855
Author(s):  
Ye Yang ◽  
Xiaoling Zhang ◽  
Shihong Li
Keyword(s):  
Physical Exercise ◽  
Physical Health ◽  
Influencing Factors ◽  
Analysis Model ◽  
Analytic Hierarchy ◽  
Factors Analysis ◽  
Factors Influencing ◽  
Training Samples ◽  
Som Network ◽  
Index Value

This paper builds a students’ physical health influencing factors analysis model based on the SOM network. First, Analytic Hierarchy Process (AHP) is adopted to confirm the weighted value of various indexes of students’ physical health influencing factors. One fourth of the weighted value of various indexes is adopted as the gradient to divide students’ physical health grades and periods, and as the input training samples for the SOM network. Following that, the SOM network after training is analyzed for its sensitivity towards factors influencing physical health. Results suggest that: (1) Duration and intensity of physical exercise is a deciding factor. According to the simulated results, a student with disqualified physical health can recover to a sound state by ensuring the index value of the above deciding factor to be above 0.6. (2) In terms of a student with good physical health, when duration and intensity of his physical exercise is “0”, his physical health will be disqualified. In order to maintain the sound physical health, the index value of duration and intensity of his physical exercise must be above 0.3.

scholarly journals CHANGE AND DEVELOPMENT LAW OF ADOLESCENTS' PHYSICAL HEALTH EXERCISE BEHAVIOR

2021 ◽  
Vol 27 (4) ◽  
pp. 386-389
Author(s):  
Liying Yao ◽  
Yanwen Lu ◽  
Yiqiong Zhang
Keyword(s):  
Physical Exercise ◽  
Physical Health ◽  
Influencing Factors ◽  
Sports Participation ◽  
Intervention Strategies ◽  
Exercise Behavior ◽  
Level Of Evidence ◽  
Exercise Habits ◽  
Starting Point ◽  
Complementary Intervention

ABSTRACT Background: The generation of individual behavior is closely related to the environment in which it is located and is easily affected by environmental factors. Objective: The thesis takes the social ecology model theory as the starting point, applies the five different levels of influencing factors in the theoretical model to the field of youth physical exercise behavior, and seeks the interrelationship between the various influencing factors. Methods: Using questionnaire surveys, interviews, and other research methods, the paper makes a simple theoretical combing and analysis of the healthy behavior ecology model, seeks the interrelationship between the influencing factors, propose complementary intervention strategies, and promote the development of adolescents’ physical exercise habits through effective ways. Results: The motivation of sports participation, the protection of physical health, family health awareness, economic and educational environment, professional quality of physical education teachers and school exercise environment and community facilities affect the direction of the development of adolescents’ physical exercise behavior. Conclusions: Only by comprehensively considering the relationship between various related factors can we better understand adolescent physical exercise development characteristics, propose complementary intervention strategies, and promote physical exercise habits effectively. Level of evidence II; Therapeutic studies - investigation of treatment results.

scholarly journals ANALYSIS AND INTERVENTION ON THE INFLUENCING FACTORS OF COLLEGE STUDENTS' PHYSICAL FITNESS

2021 ◽  
Vol 27 (spe) ◽  
pp. 11-13
Author(s):  
Peng Bo
Keyword(s):  
College Students ◽  
Physical Health ◽  
Influencing Factors ◽  
Evaluation Index ◽  
Sports Facilities ◽  
School Factors ◽  
Analytic Hierarchy ◽  
Factors Affecting ◽  
School Sports ◽  
Sports Venues

ABSTRACT Enhancing the physical health of college students is the fundamental guarantee of cultivating high-quality talents. In order to understand the influencing factors of college students' physical health and carry out targeted intervention, this study aims to analyze the factors affecting college students' physical health. Through the construction of physical health evaluation index and its influencing factors evaluation index, the importance of different indicators is evaluated by using the analytic hierarchy process, and a questionnaire about college students' physical health and its influencing factors is designed. The results show that the factors affecting college students' physical health include students' own factors, school factors, and others. At the same time, the insufficient construction of public sports facilities and the lack of first-class sports venues and equipment are also the reasons for the decline of college students' physique. Therefore, we can intervene in the students' physical health from the aspects of raising the students' awareness about physical exercise and Ensuring the construction of school sports facilities. It is hoped that this study can provide some reference for the empirical analysis and intervention research on the influencing factors of college students' physical health.

Influencing Factors Analysis for Failure Risk of Upstream Revetment of Existing Levees

2011 ◽  
Vol 250-253 ◽  
pp. 2843-2847 ◽  
Author(s):  
Yan Hong Gao ◽  
Jun Zhi Zhang
Keyword(s):  
Risk Analysis ◽  
Influencing Factors ◽  
Load Effect ◽  
Factors Analysis ◽  
Factors Influencing ◽  
Failure Risk ◽  
Analysis Theory ◽  
Proposed Model ◽  
Calculation Results ◽  
Main Factors

According to risk analysis theory, a model of analysis for failure risk of upstream revetment of existing levees is proposed in this paper. Based on the model, the load effect and generalized resistance for the failure risk of upstream revetment of existing levees are analyzed, and then the influencing factors of the failure risk of upstream revetment are studied. The calculation results show that the proposed model is workable and effective for analysis of the failure risk of upstream revetment of existing levees, and the main factors influencing failure risk of existing upstream revetment are the randomness of the existing effective thickness of upstream revetment and ratio mean of upstream slope of the existing levees.

scholarly journals EMPIRICAL ANALYSIS AND INTERVENTION RESEARCH ON THE INFLUENCING FACTORS OF COLLEGE STUDENTS’ PHYSICAL HEALTH

2021 ◽  
Vol 27 (spe) ◽  
pp. 24-27
Author(s):  
Bo Xu
Keyword(s):  
College Students ◽  
Analytic Hierarchy Process ◽  
Physical Health ◽  
Influencing Factors ◽  
Living Standards ◽  
School Students ◽  
Analytic Hierarchy ◽  
Factors Affecting ◽  
School Sports ◽  
Hierarchy Process

ABSTRACT Since the reform and opening up, China’s national living standards have gradually improved, but the current physical health level of college students has not increased with the improvement of living standards. The physical health of college students — as high-quality talents of the country — is related to the future of the country and the nation,. In order to explore the influencing factors of college students’ physical health, the analytic hierarchy process (AHP) was used to evaluate the factors affecting students’ physical health. This study analyzes the index of students’ physical health through the method of literature, then revises the evaluation index through expert analysis and analytic hierarchy process, and verifies it through examples. The results show that the final score of the school students’ physical health is 81.55, of which the school factor has the greatest impact on the students’ physical health, and the school factor score is far from the expected score. We can promote the development of students’ physical exercise and improve the level of students’ physical health through the improvement of school sports management. This study provides reference for the healthy development of public sports students in China.

scholarly journals INFLUENCING FACTORS OF COLLEGE STUDENTS’ PHYSICAL HEALTH UNDER THE INTERVENTION OF FOOTBALL

2021 ◽  
Vol 27 (spe) ◽  
pp. 34-36
Author(s):  
Jin Gang
Keyword(s):  
College Students ◽  
Physical Health ◽  
Influencing Factors ◽  
Autocorrelation Function ◽  
Evaluation System ◽  
Evaluation Method ◽  
The Body ◽  
Fuzzy Evaluation ◽  
Analysis Model ◽  
Intelligent Technology

ABSTRACT The current football can effectively exercise the body of college students and improve their physical health. How to use modern intelligent technology to perform quantitative research on the influencing factors of football on college students’ physical health is the current development trend. Based on this, this paper studies the influencing factors of college students’ physical health under the intervention of football. First of all, this paper puts forward an analysis model of college students’ physical health based on the sarsa algorithm. The autocorrelation function is used to simulate and process the students’ physical information. Through the maximum value of the autocorrelation function curve in the detection process, the detection signal is restored, then the error of the sarsa algorithm is analyzed. Secondly, this paper expounds the influence factors of sarsa algorithm on students’ physical health in football. Fuzzy evaluation method and analytic hierarchy process are used in the evaluation. Aiming at the shortcomings of AHP, the improved sarsa algorithm is used for comprehensive analysis, and an adaptive simulation evaluation system is established. Finally, the effectiveness of the sarsa algorithm in this system is verified by many football experiments.

Influencing Factors Analysis of House Prices Based on Multiple Linear Regression

2013 ◽  
Vol 415 ◽  
pp. 722-725 ◽  
Author(s):  
Cheng Wang
Keyword(s):  
Linear Regression ◽  
Multiple Linear Regression ◽  
Influencing Factors ◽  
House Prices ◽  
Supply And Demand ◽  
Housing Prices ◽  
Influence Factors ◽  
Analysis Model ◽  
Factors Analysis ◽  
The Stability

Housing problems are related to the vital interests of people and the stability of community. The stability of housing prices is directly related to the level of people's life and the development of the national economy. This paper analyzed the influence factors for market supply and demand of commodity housing, and established price influence factors analysis model based on multiple linear regression. By the empirical analysis, the main influencing factors of housing prices are got, and some policy recommendations of price control are given based on these main influencing factors.

Prioritization of critical risk influencing factors in quantitative risk analyses for offshore petroleum installations

2020 ◽  
pp. 1748006X2094336
Author(s):  
Xingwei Zhen ◽  
Jan Erik Vinnem
Keyword(s):  
Risk Analysis ◽  
Influencing Factors ◽  
Influencing Factor ◽  
Pairwise Comparison ◽  
Organizational Factors ◽  
Sensitivity Study ◽  
Analysis Model ◽  
Analytic Hierarchy ◽  
Quantitative Risk Analysis ◽  
The Status

Comprehensive and detailed investigations of various major offshore accidents have shown that multifarious risk influencing factors including technical, human, and organizational factors have a significant impact on the nonlinear accident sequences. Parallel efforts are being made to develop quantitative risk analysis models involving risk influencing factors. It is recognized that in order to keep quantitative risk analyses in a manageable size, it is essential to restrict the number of risk influencing factors for each failure event. This article describes an effort to prioritize critical risk influencing factors for offshore maintenance work. A prioritization index integrating the weight and the status of each risk influencing factor is developed to determine the most appropriate prioritization. A hierarchy tree is developed to structure the identified risk influencing factors. The unified fuzzy scoring criterion is established for evaluating the risk influencing factors status. The fuzzy analytic hierarchy process approach stressing the consistency of the fuzzy pairwise comparison is applied to evaluate the priority of each risk influencing factor. A sensitivity study is conducted to investigate the criticality of risk influencing factors. The case study demonstrates that the proposed method can be a practical tool for prioritizing critical risk influencing factors effectively for all failure events in the quantitative risk analysis model. The method can also be useful in handling uncertainties arising in quantitative risk analyses.

scholarly journals Analysis of Medication Adherence and Its Influencing Factors in Patients with Schizophrenia in the Chinese Institutional Environment

2021 ◽  
Vol 18 (9) ◽  
pp. 4746
Author(s):  
Wei Yu ◽  
Jie Tong ◽  
Xirong Sun ◽  
Fazhan Chen ◽  
Jie Zhang ◽  
...  
Keyword(s):  
Quality Of Life ◽  
Medication Adherence ◽  
Activities Of Daily Living ◽  
Influencing Factors ◽  
Self Efficacy ◽  
Daily Living ◽  
Institutional Environment ◽  
Factors Influencing ◽  
Quality Of Life Scale

Background: Factors related to medication adherence in patients with schizophrenia have always been key to the treatment and rehabilitation of these patients. However, the treatment modes in different countries are not the same, and there is no research on the factors influencing medication adherence under different mental health service modes. Objectives: The purpose of this study was to explore medication adherence and its influencing factors in patients with schizophrenia in the Chinese institutional environment. Methods: We conducted a cross-sectional study of hospitalized persons living with schizophrenia from November 2018 to January 2019. A systematic sampling method was used to select 217 hospitalized persons living with schizophrenia. The Medication Adherence Rating Scale (MARS), Positive and Negative Syndrome Scale (PANSS), General Self-Efficacy Scale (GSES), Schizophrenia Quality of Life Scale (SQLS), and Scale of Social Skills for Psychiatric Inpatients (SSPI) were used to explore medication compliance and its influencing factors in the Chinese institutional environment. Results: The descriptive analysis and ANOVA showed that there were no significant differences in medication adherence when assessed by demographic characteristics such as sex, marital status, and education level (p > 0.05). A correlation analysis showed that there was no significant correlation between medication adherence and mental symptoms (p > 0.05) but that there was a positive correlation with self-efficacy, quality of life, and activities of daily living (p < 0.01). The linear regression analysis showed that self-efficacy, psychosocial factors, symptoms/side effects, and activities of daily living had significant effects on medication adherence (F = 30.210, p < 0.001). Conclusions: Our findings show that the self-efficacy, quality of life, and social function of patients with schizophrenia are important self-factors influencing medication adherence in the Chinese institutional environment.

scholarly journals Socioeconomic Risks and Their Impacts on Ecological River Health in South Korea: An Application of the Analytic Hierarchy Process

2021 ◽  
Vol 13 (11) ◽  
pp. 6287
Author(s):  
Suyeon Kim ◽  
Sang-Woo Lee ◽  
Se-Rin Park ◽  
Yeeun Shin ◽  
Kyungjin An
Keyword(s):  
South Korea ◽  
Socioeconomic Factors ◽  
Ecosystem Health ◽  
Relative Importance ◽  
River Ecosystem ◽  
River Health ◽  
Analytic Hierarchy ◽  
Factors Affecting ◽  
Factors Influencing ◽  
Hierarchy Process

It is imperative to develop a methodology to identify river impairment sources, particularly the relative impact of socioeconomic sources, to enhance the efficiency of various river restoration schemes and policies and to have an internal diagnosis system in place. This study, therefore, aims to identify and analyze the relative importance of the socioeconomic factors affecting river ecosystem impairment in South Korea. To achieve this goal, we applied the Analytical Hierarchy Process (AHP) to evaluate expert judgement of the relative importance of different socioeconomic factors influencing river ecosystem impairment. Based on a list of socioeconomic factors influencing stream health, an AHP questionnaire was prepared and administered to experts in aquatic ecology. Our analysis reveals that secondary industries form the most significant source of stream ecosystem impairment. Moreover, the most critical socioeconomic factors affecting stream impairment are direct inflow pollution, policy implementation, and industrial wastewater. The results also suggest that the AHP is a rapid and robust approach to assessing the relative importance of different socioeconomic factors that affect river ecosystem health. The results can be used to assist decision makers in focusing on actions to improve river ecosystem health.

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