Adaptive Improvement of Genetic Algorithms and Their Application in Civil Engineering

Building structure design and construction play an important role in the application of civil engineering, but there is a problem that the application scope is not comprehensive. Traditional neural network algorithms cannot solve civil engineering problems in applications in civil engineering, and the effect is not ideal. Therefore, the application of adaptive improved genetic algorithm in civil engineering is proposed, and the application in civil engineering is analyzed. Firstly, the theory of improvement strategy is used to locate the influencing factors, and the indicators is divided according to the requirements of building structure design and construction, so as to reduce the interference factors in building structure design and construction. Then, the improvement strategy theory is used to form an adaptive improvement genetic algorithm building structure design and construction scheme, and the building structure design and construction results is comprehensively analyzed. The MATLAB simulation results show that under certain evaluation criteria, the adaptive improvement genetic algorithm is superior to the traditional neural network algorithm in terms of building structure design and construction accuracy, building structure design and construction influencing factor time.