An Intelligent Optimization Method for Large Underground Space Construction Scheme Under Low Carbon Target
The construction of large underground spaces is an important field of transformation and upgra-ding of the construction industry.In the construction process of large underground spaces,how to obtain the optimal construction scheme and achieve the goal of green environmental protection is an urgent problem to be solved.Aiming at low carbon,the study proposed an intelligent optimization method for large under-ground space construction.According to the calculation method of carbon emissions,the construction scheme optimization framework was formed,and the key factors affecting the construction energy consump-tion were obtained.Based on the analysis of key factors,the influence mechanism of various components and construction paths on carbon emissions was clarified.Driven by the improved Dijkstra algorithm,an in-telligent optimization method of construction path was formed.On this basis,the BP neural network opti-mized by genetic algorithm formed the coupling relationship between carbon emission and hoisting scheme.The optimal construction scheme was obtatined accurately under the low-carbon goal.Taking the construc-tion site of the three major building shared facilities project of the city sub-center as an example,the case analysis was carried out to verify the feasibility of the proposed method.By analyzing the construction car-bon emissions,the best construction path was formed.
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