Abstract
The existing social talent governance algorithms have a number of issues such as slow convergence rate, relatively low data accuracy, recall rate, and low anti-interference. To address these problems, this paper proposes a research on social talent governance algorithm based on genetic algorithm. We discuss the difference between the traditional and the genetic algorithms and determine the implementation process of genetic algorithm. On this basis, the excellent individuals are determined by independent computing fitness, and the initialization population is designed according to the individual similarity threshold. After the population is defined, the roulette and deterministic sampling selection method are integrated to clarify the selection calculation process. Based on the calculation results, we design the crossover operator by segmented single-point crossover between individuals. The mutation operator is designed by segmented mutation of different gene segments according to the calculation results. The results are incorporated into the simulated annealing acceptance probability to conduct simulated annealing for the individuals after the cross-mutation operation and set relevant conditions after the end of the algorithm. We seek the optimal solution of the data within the number of iterations and finally realize the whole process of social talent governance algorithm. The experimental results show that the proposed algorithm has fast convergence rate, high data precision and recall, and has certain feasibility.
Highlights
Since the 18th National Congress, social governance has officially replaced social management and become one of the important aspects of the construction of socialism with Chinese characteristics. e ird Plenary Session of the 18th CPC Central Committee put forward the social governance concept of optimizing social management for the first time
Promoting the construction of social governance system, innovating social governance methods, and effectively improving the level of public governance of the whole society have become the focus of social governance. e report of the 19th national congress attaches great importance to social governance, clearly points out the problems existing in China’s current social governance, and puts forward “building a social governance pattern of co construction, CO governance and sharing” [2]
In the field of social governance, talent governance has become the top priority of current social development, and fundamentally speaking, social governance is mainly the governance of “people” [3]
Summary
Since the 18th National Congress, social governance has officially replaced social management and become one of the important aspects of the construction of socialism with Chinese characteristics. e ird Plenary Session of the 18th CPC Central Committee put forward the social governance concept of optimizing social management for the first time. A number of research studies focus on the use of genetic algorithms to present solution to complex problems. (4) e results are incorporated into the simulated annealing acceptance probability to conduct simulated annealing for the individuals after the crossmutation operation, set relevant conditions after the end of the algorithm, seek the optimal solution of the data within the number of iterations, and realize the whole process of social talent governance algorithm. Step 4: integrate the results into the simulated annealing acceptance probability, conduct simulated annealing for the individuals after crossmutation operation, set relevant conditions after the end of the algorithm, seek the optimal solution of the data within the number of iterations, and realize the whole process of social talent governance algorithm.
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