Design of Safety Management System for Housing Construction System Based on Genetic Algorithm

In order to explore the potential correlation among the factors that cause major construction safety accidents, a mining pattern of association rules based on genetic algorithm is constructed. The appropriate fitness function is established by combining the support degree and confidence rate. The adaptive crossover and mutation probability are used to find the common item set, and a large number of misleading rules are introduced to filter the interest rate. The experimental results show that the model effectively overcomes the shortcomings of genetic algorithm, such as premature, slow convergence and repeated scanning data sets, resulting in low efficiency. This article first introduces genetic algorithms, their theoretical basis, basic principles, characteristics, and applications. Subsequently, the description and components of the standard genetic algorithm were proposed, and its operation process and application steps were described. Subsequently, the implementation technology and algorithm design of genetic algorithms were introduced. Finally, an example was provided to illustrate the process of implementing genetic algorithms in application creation. This fully reflects the important role and broad application prospects of genetic algorithms in the development of innovative architectural design.