Evaluation method of outdoor thermal comfort in urban high-density area based on deep learning 3D reconstruction

Abstract

The invention discloses a method for evaluating outdoor thermal comfort in urban high-density areas based on deep learning three-dimensional reconstruction, including: acquiring remote sensing image data of urban high-density areas; preprocessing the remote sensing image data of urban high-density areas under the Python integration platform, Obtain the remote sensing image data set; establish a neural network model based on CNN‑LSTM, and train the model using the stochastic gradient descent method; input the remote sensing image data set into the trained neural network model to obtain a 3D reconstruction model of urban high-density areas ; Perform computer simulation on the three-dimensional information model of urban high-density areas to generate an environmental information model of urban high-density areas; use ENVI‑met to simulate and analyze the environmental information model of urban high-density areas, and evaluate outdoor thermal comfort based on the data simulation analysis results. This method solves the bottleneck problem of building environmental information modeling accuracy and efficiency in outdoor thermal comfort evaluation of urban high-density areas.

Description

technical field [0001] The invention relates to the field of deep learning technology, in particular to a method for evaluating outdoor thermal comfort in urban high-density areas based on three-dimensional reconstruction of deep learning. Background technique [0002] With the acceleration of urbanization, the heat island effect in urban high-density areas is intensified. Efficient and accurate evaluation of outdoor thermal comfort in urban high-density areas plays an important role in guiding urban planning and urban design. Existing thermal comfort evaluation methods in urban high-density areas need to establish an outdoor thermal comfort evaluation model based on urban building approval data and field measurement data, which has low modeling efficiency, easy loss of building surrounding environment information, and delayed update of existing building renovation and expansion These problems affect the accuracy and efficiency of thermal comfort evaluation in urban high-de...

AI Technical Summary

Problems solved by technology

Existing thermal comfort evaluation methods in urban high-density areas need to establish an outdoor thermal comfort evaluation model based on urban building approval data and field measurement data, which has low modeling efficiency, easy loss of building surrounding environment information, and delayed update of existing building renovation and expansion These problems have affected the improvement of the accuracy and efficiency of thermal comfort evaluation in urban high-density areas, and restricted its application in the planning and design of urban high-density areas.

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