Objective. The mainstream development trend in the era of intelligent sports. At present, with the rapid development of science and technology, it is absolutely wise to combine group intelligence with community intelligent sports services for the elderly. Group intelligence has opened a new era of intelligent sports service. Group intelligence has become an important factor in the development and growth of community intelligent sports service for the elderly and has become a hot topic at present. However, intelligence has encountered difficulties on the road of development. At present, the aging of the population is getting worse and worse, and the elderly have higher and higher requirements for fitness and leisure services, which leads to the need for sports services to be continuously strengthened. The distribution of resources is uneven, the data is not clear enough, and the swarm intelligence algorithm is not perfect. With the adaptation of the elderly to intelligence, more intelligent, concise, and personalized services need to be developed. The most important method is to optimize the swarm intelligence algorithm continuously. In this paper, PSO algorithm is optimized and HCSSPSO algorithm is proposed. HCSSPSO algorithm is a combination of PSO algorithm and clonal selection strategy, and test simulation experiments, PSO algorithm, CLPSO algorithm, and HCSSPSO algorithm for comparison. From the experimental results, HCSSPSO algorithm has better convergence speed and stability, whether it is data or comparison graph. The data optimized by HCSSPSO algorithm is higher than the original data and the other two algorithms in terms of satisfaction and resource allocation.
Research on Resource Allocation and Optimization of Community Intelligent Sports Service for the Elderly Based on Group Intelligence
