Comprehensive Evaluation of Building Energy Efficiency Based on Chaotic Neural Network

In view of the limitations of traditional image recognition algorithms in the comprehensive evaluation of building energy efficiency, a comprehensive evaluation scheme of energy conservation based on chaotic neural network was proposed. Firstly, the influencing factors is accurately located through the complex neuron theory, and the indicators is reasonably divided to reduce interference, and the chaotic neural network is used to construct a comprehensive evaluation scheme for energy saving. Experimental results show that under certain evaluation criteria, the proposed scheme is superior to the traditional image recognition algorithm in terms of the accuracy of comprehensive evaluation of energy saving and the processing time of influencing factors, and has obvious advantages. The comprehensive evaluation of energy conservation plays an extremely important role in construction projects, which can accurately predict and optimize the growth characteristics and product generation of construction projects. However, traditional image recognition algorithms have certain limitations in solving building evaluation simulation problems, especially when dealing with complex problems. In this paper, a comprehensive evaluation scheme of energy conservation based on chaotic neural network is proposed to better solve this problem. In this scheme, the influencing factors is accurately located through the complex neuron theory, so as to determine the division of indicators, and the chaotic neural network is used to construct the scheme. Experimental results show that under certain evaluation criteria, the accuracy and speed of the scheme is significantly improved for different problems, and it has better performance. Therefore, the simulation scheme based on chaotic neural network can better solve the limitations of traditional image recognition algorithms and improve the simulation accuracy and efficiency in the comprehensive evaluation of building energy efficiency.