Public Intelligent Algorithm of Resource Allocation and Benefit Maximization of Civil Sports Organizations - Zhou, Xuehua; Guo, Xuesong (International Journal of Intelligent Systems and Applications in Engineering, 2023)
Civil sports organizations play a vital role in promoting physical activity, community engagement, and well-being. Efficient resource allocation and benefit maximization are paramount for the sustainable growth and impact of such organizations. This research paper presents an innovative approach to address these challenges by leveraging a Public Intelligence Algorithm (PIA) to optimize resource allocation and enhance the benefits offered by civil sports organizations. With the designed PIA algorithm the chain rules are implemented for the estimation of the feature set. The central focus of this study revolves around the application of a Mass Intelligence Algorithm, a novel approach that combines the collective intelligence of diverse stakeholders, including athletes, coaches, volunteers, and administrators. PIA enables real-time analysis of data from multiple sources to guide resource allocation decisions and maximize the benefits provided to the community. The proposed PIA, involve data aggregation, machine learning, and predictive modeling to optimize the allocation of resources such as funding, facilities, coaching, and event planning. This data-driven approach ensures that resources are allocated efficiently to support the diverse needs and preferences of the community. The analysis expressed that the proposed PIA model with the chain rule increases the performance of the sports organization with effective allocation of resources. The findings stated the transformative potential of this innovative approach in optimizing resource allocation and benefit maximization within civil sports organizations.