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In view of the increasing importance of sports to people and the impact of COVID-19 on people’s lives, home-based exercise has become a popular choice for people to keep fit due to its unique advantages and its popularity is expected to keep growing in the future. Therefore, it is necessary to determine the development direction of home-based exercise and put in the corresponding efforts. However, there is currently a lack of research on all aspects of home-based exercise. The purpose of this research was to investigate the effective sustainable development strategy of home-based exercise in China through a SWOT (Strengths, Weaknesses, Opportunities and Threats) and AHP (Analytic Hierarchy Process) hybrid model. Thirteen factors corresponding to the SWOT analysis were identified through a literature review and expert opinions. The results show that in China the advantages and potential outweigh the weaknesses and threats of home-based exercise. Home-based exercise should grasp the external development opportunities and choose the SO development strategic type that combines internal strengths and external opportunities. As the core for the development of home-based exercise, this strategy should be given priority. To sum up, home-based exercise is believed to have a bright future.

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Summary Considering the limitations of the traditional hydraulic‐seasonal‐time (HST) model, this study proposes a hybrid modeling method for the deformation prediction of high concrete dams during the operational period. First, the elastic finite element (FE) method is applied to simulate the interactive effects of structural properties, topography, geology, and high hydrostatic load on the deformation behaviour of high concrete dams in operating conditions. The hybrid model of hydrostatic pressure deformation is established. The hybrid hydraulic‐seasonal‐time (HHST) model is proposed. Second, the self‐adaptive stochastic inertia weight, dynamic learning factors, and velocity and position parameters are introduced to improve the particle swarm optimization (PSO) algorithm. The hybrid prediction approach is developed through the comprehensive application of the HHST model and the improved PSO algorithm. The proposed methodology is adopted for the Jinping I project, which is the highest concrete arch dam in the world. The analysis results indicate that the model accuracy is good and that the model performance is promoted.

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